Index (wekaDeeplearning4j 1.7.2 API)

A B C D E F G H I K L M N O P R S T U V W X Z

A

AbstractCNNSaliencyMapGenerator - Class in weka.dl4j.interpretability: Generic class for a saliency map generator.
AbstractCNNSaliencyMapGenerator() - Constructor for class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
AbstractCNNSaliencyMapWrapper - Class in weka.dl4j.interpretability: WEKA Wrapper for a Saliency Map Generator (e.g., ScoreCAM).
AbstractCNNSaliencyMapWrapper() - Constructor for class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
AbstractDropout<T extends org.deeplearning4j.nn.conf.dropout.IDropout> - Class in weka.dl4j.dropout: Abstract dropout class.
AbstractDropout() - Constructor for class weka.dl4j.dropout.AbstractDropout
AbstractInstanceIterator - Class in weka.dl4j.iterators.instance: An abstract iterator that wraps DataSetIterators around Weka Instances.
AbstractInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.AbstractInstanceIterator
AbstractProgressBar - Class in weka.core.progress: Handles common tasks between the GUI and Command line progress bar.
AbstractProgressBar(double, String) - Constructor for class weka.core.progress.AbstractProgressBar: Create a new progress bar.
AbstractSequenceInstanceIterator - Class in weka.dl4j.iterators.instance.sequence: Marker class to differentiate between iterators for Dl4jMlpClassifier and RnnSequenceClassifier.
AbstractSequenceInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.AbstractSequenceInstanceIterator
AbstractTextEmbeddingIterator - Class in weka.dl4j.iterators.instance.sequence.text: Abstract text iterator that provides variables and methods for text processing.
AbstractTextEmbeddingIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
AbstractWeightNoise<T extends org.deeplearning4j.nn.conf.weightnoise.IWeightNoise> - Class in weka.dl4j.weightnoise: Abstract weight noise class.
AbstractWeightNoise() - Constructor for class weka.dl4j.weightnoise.AbstractWeightNoise
AbstractZooModel - Class in weka.dl4j.zoo: This class contains the logic necessary to load the pretrained weights for a given zoo model It also handles the addition/removal of output layers to enable training the model in DL4J.
AbstractZooModel() - Constructor for class weka.dl4j.zoo.AbstractZooModel
Activation<T extends org.nd4j.linalg.activations.IActivation> - Class in weka.dl4j.activations: Abstract activation class
Activation() - Constructor for class weka.dl4j.activations.Activation
ActivationCube - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationCube that implements WEKA option handling.
ActivationCube() - Constructor for class weka.dl4j.activations.ActivationCube
ActivationELU - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationELU that implements WEKA option handling.
ActivationELU() - Constructor for class weka.dl4j.activations.ActivationELU
ActivationHardSigmoid - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationHardSigmoid that implements WEKA option handling.
ActivationHardSigmoid() - Constructor for class weka.dl4j.activations.ActivationHardSigmoid
ActivationHardTanH - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationHardTanH that implements WEKA option handling.
ActivationHardTanH() - Constructor for class weka.dl4j.activations.ActivationHardTanH
ActivationIdentity - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationIdentity that implements WEKA option handling.
ActivationIdentity() - Constructor for class weka.dl4j.activations.ActivationIdentity
ActivationLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's ActivationLayer layer that implements WEKA option handling.
ActivationLayer() - Constructor for class weka.dl4j.layers.ActivationLayer: Constructor for setting some defaults.
ActivationLReLU - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationLReLU that implements WEKA option handling.
ActivationLReLU() - Constructor for class weka.dl4j.activations.ActivationLReLU
ActivationRationalTanh - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationRationalTanh that implements WEKA option handling.
ActivationRationalTanh() - Constructor for class weka.dl4j.activations.ActivationRationalTanh
ActivationReLU - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationReLU that implements WEKA option handling.
ActivationReLU() - Constructor for class weka.dl4j.activations.ActivationReLU
ActivationRReLU - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationRReLU that implements WEKA option handling.
ActivationRReLU() - Constructor for class weka.dl4j.activations.ActivationRReLU
ActivationSigmoid - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationSigmoid that implements WEKA option handling.
ActivationSigmoid() - Constructor for class weka.dl4j.activations.ActivationSigmoid
ActivationSoftmax - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationSoftmax that implements WEKA option handling.
ActivationSoftmax() - Constructor for class weka.dl4j.activations.ActivationSoftmax
ActivationSoftPlus - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationSoftPlus that implements WEKA option handling.
ActivationSoftPlus() - Constructor for class weka.dl4j.activations.ActivationSoftPlus
ActivationSoftSign - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationSoftSign that implements WEKA option handling.
ActivationSoftSign() - Constructor for class weka.dl4j.activations.ActivationSoftSign
ActivationSwish - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationSwish that implements WEKA option handling.
ActivationSwish() - Constructor for class weka.dl4j.activations.ActivationSwish
ActivationTanH - Class in weka.dl4j.activations: A version of DeepLearning4j's ActivationTanH that implements WEKA option handling.
ActivationTanH() - Constructor for class weka.dl4j.activations.ActivationTanH
AdaDelta - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's AdaDelta.
AdaDelta() - Constructor for class weka.dl4j.updater.AdaDelta
AdaGrad - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's AdaGrad.
AdaGrad() - Constructor for class weka.dl4j.updater.AdaGrad
Adam - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's Adam.
Adam() - Constructor for class weka.dl4j.updater.Adam
AdaMax - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's AdaMax.
AdaMax() - Constructor for class weka.dl4j.updater.AdaMax
addIterationIncrementListener(IterationIncrementListener) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator: Add an event listener to the iterations increment event.
addIterationsFinishedListeners(IterationsFinishedListener) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator: Add an event listener to the iterations finished event.
addIterationsStartedListener(IterationsStartedListener) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator: Add an event listener to the iterations started event.
addTransformationLayerName(String) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Adds a new transformation layer for the filter to use.
AlgoMode - Enum in weka.dl4j.enums: Proxy Enum for ConvolutionMode.
allLabels() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
AlphaDropout - Class in weka.dl4j.dropout: Gaussian dropout implementation.
AlphaDropout() - Constructor for class weka.dl4j.dropout.AlphaDropout
ApiWrapper<T> - Interface in weka.dl4j: A general interface to access a backend object of a certain deeplearning4j class which is wrapped in a class to make it usable in weka.
ApiWrapperUtil - Class in weka.dl4j: This utility class manages loading the appropriate wrapping class for a given backend object
ApiWrapperUtil() - Constructor for class weka.dl4j.ApiWrapperUtil
appendClasses(INDArray, Instances) - Static method in class weka.dl4j.Utils: Appends the input Instances classes to the INDArray.
apply() - Method in class weka.core.LogConfiguration: Apply the logging configuration.
ArffMetaDataLabelGenerator - Class in weka.dl4j: A LabelGenerator based on the file path in the Arff-Meta dataset
ArffMetaDataLabelGenerator(Instances, String) - Constructor for class weka.dl4j.ArffMetaDataLabelGenerator: Default constructor which sets the metaData
arithmeticUnderflow(INDArray) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Checks the array (as output from ComputationGraph.outputSingle()) for arithmetic underflow
asyncSupported() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Whether the iterator can be used asynchronously.
asyncSupported() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
asyncSupported() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator

B

batch() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: The size of the mini batches.
batch() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
batch() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
BatchNormalization - Class in weka.dl4j.layers: A version of DeepLearning4j's BatchNormalization layer that implements WEKA option handling.
BatchNormalization() - Constructor for class weka.dl4j.layers.BatchNormalization: Constructor for setting some defaults.
BinomialDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's BinomialDistribution that implements WEKA option handling.
BinomialDistribution() - Constructor for class weka.dl4j.distribution.BinomialDistribution
BroadcastLambdaLayer - Class in weka.dl4j.layers: A WEKA option handler class for the CustomBroadcast layer, required to use EfficientNet.
BroadcastLambdaLayer() - Constructor for class weka.dl4j.layers.BroadcastLambdaLayer: Constructor for setting some defaults.
build() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator.Builder: Build the iterator.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: The method used to train the classifier.
Builder() - Constructor for class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator.Builder
builder() - Method in class weka.dl4j.NeuralNetConfiguration: Deliver access to the internal builder

C

CacheMode - Enum in weka.dl4j.enums: Cache modes for datasetiterators.
call() - Method in interface weka.dl4j.VoidCallable
CenterLossOutputLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's CenterLossOutputLayer layer that implements WEKA option handling.
CenterLossOutputLayer() - Constructor for class weka.dl4j.layers.CenterLossOutputLayer: Constructor for setting some defaults.
CharacterNGramTokenizerFactory - Class in weka.dl4j.text.tokenization.tokenizer.factory: A DeepLearning4j's TokenizerFactory interface for Weka core tokenizers.
CharacterNGramTokenizerFactory() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
CharacterNGramTokenizerFactoryImpl - Class in weka.dl4j.text.tokenization.tokenizer.factory.impl: A DeepLearning4j's TokenizerFactory interface for Weka core tokenizers.
CharacterNGramTokenizerFactoryImpl() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
check() - Method in class weka.dl4j.IsGPUAvailable: Main Entrypoint: Check whether WekaDeeplearning4j can detect a GPU backend.
checkArgs() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Check the arguments for the explorer.
checkIfRunByGUI() - Method in class weka.core.progress.ProgressManager: Checks the stacktrace for a call to anything in the weka.gui package.
Checksums - Static variable in class weka.dl4j.zoo.keras.KerasConstants: Checksums of model files.
ClassmapType - Enum in weka.dl4j.inference: Built-in class maps for WDL4J.
ClassSelector - Class in weka.gui.explorer: Class selector panel.
ClassSelector(JPanel, String[]) - Constructor for class weka.gui.explorer.ClassSelector: Init the ClassSelector panel.
clearTransformationLayers() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Clear the transformation layers to be used by the filter.
clone() - Method in class weka.dl4j.schedules.ConstantSchedule.ConstantScheduleImpl
CnnSentenceDataSetIterator - Class in weka.dl4j.iterators.dataset.sequence.text.cnn: CnnSentenceDataSetIterator extension to Deeplearning4j implementation.
CnnSentenceDataSetIterator.Builder - Class in weka.dl4j.iterators.dataset.sequence.text.cnn: CnnSentenceDataSetIterator.Builder implementation that supports stopwords.
CnnTextEmbeddingInstanceIterator - Class in weka.dl4j.iterators.instance.sequence.text.cnn: Iterator that constructs datasets from text data for convolutional networks.
CnnTextEmbeddingInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator
CnnTextFilesEmbeddingInstanceIterator - Class in weka.dl4j.iterators.instance.sequence.text.cnn: Iterator that constructs datasets from text data given as a set of files.
CnnTextFilesEmbeddingInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
CollectionLabeledSentenceProvider - Class in weka.dl4j.iterators.provider: Extend CollectionLabeledSentenceProvider from DL4J to support setting numClasses dynamically for regression tasks.
CollectionLabeledSentenceProvider(List<String>, List<String>, int) - Constructor for class weka.dl4j.iterators.provider.CollectionLabeledSentenceProvider
CommandLineProgressBar - Class in weka.core.progress: Command line implementation of a progress bar.
CommandLineProgressBar(double, String) - Constructor for class weka.core.progress.CommandLineProgressBar: Instantiate a new progress bar.
commandLineProgressTest() - Static method in class weka.examples.WekaDeeplearning4jExamples
CommonPreProcessor - Class in weka.dl4j.text.tokenization.preprocessor: A wrapper that extends the PreProcessor API for CommonPreProcessorImpl.
CommonPreProcessor() - Constructor for class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor
CommonPreProcessorImpl - Class in weka.dl4j.text.tokenization.preprocessor.impl: A serializable version of DeepLearning4j's CommonPreProcessor.
CommonPreProcessorImpl() - Constructor for class weka.dl4j.text.tokenization.preprocessor.impl.CommonPreProcessorImpl
computeScore(ComputationGraph, DataSetIterator) - Static method in class weka.dl4j.Utils: Compute the model score on a given iterator.
ConstantDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's ConstantDistribution that implements WEKA option handling.
ConstantDistribution() - Constructor for class weka.dl4j.distribution.ConstantDistribution
ConstantSchedule - Class in weka.dl4j.schedules: Constant schedule for learning rates.
ConstantSchedule() - Constructor for class weka.dl4j.schedules.ConstantSchedule
ConstantSchedule.ConstantScheduleImpl - Class in weka.dl4j.schedules
ConstantScheduleImpl() - Constructor for class weka.dl4j.schedules.ConstantSchedule.ConstantScheduleImpl
ConstantScheduleImpl(double) - Constructor for class weka.dl4j.schedules.ConstantSchedule.ConstantScheduleImpl
convertToInstances(INDArray, Instances, Map<String, Long>) - Static method in class weka.dl4j.Utils: Converts the newly transformed instances to an Instances object.
ConvolutionalIterator - Interface in weka.dl4j.iterators.instance.api: Interface for objects for which convolution can be applied.
ConvolutionInstanceIterator - Class in weka.dl4j.iterators.instance: Converts the given Instances object into a DataSet and then constructs and returns a DefaultDataSetIterator.
ConvolutionInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
ConvolutionLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's ConvolutionLayer that implements WEKA option handling.
ConvolutionLayer() - Constructor for class weka.dl4j.layers.ConvolutionLayer: Constructor for setting some defaults.
ConvolutionMode - Enum in weka.dl4j.enums: Proxy Enum for ConvolutionMode.
copyNominalAttribute(Attribute) - Static method in class weka.dl4j.Utils: Copies the attribute name and values of a given nominal attribute.
countTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer
countTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer
create(IActivation) - Static method in class weka.dl4j.activations.Activation: Create an API wrapped schedule from a given ISchedule object.
create(Distribution) - Static method in class weka.dl4j.distribution.Distribution: Create an API wrapped layer from a given layer object.
create(IDropout) - Static method in class weka.dl4j.dropout.AbstractDropout: Create an API wrapped layer from a given layer object.
create(Layer) - Static method in class weka.dl4j.layers.Layer: Create an API wrapped layer from a given layer object.
create(ILossFunction) - Static method in class weka.dl4j.lossfunctions.LossFunction: Create an API wrapped schedule from a given ILossFunction object.
create(ISchedule) - Static method in class weka.dl4j.schedules.Schedule: Create an API wrapped schedule from a given ISchedule object.
create(StepFunction) - Static method in class weka.dl4j.stepfunctions.StepFunction: Create an API wrapped schedule from a given ISchedule object.
create(TokenPreProcess) - Static method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess: Create an API wrapped schedule from a given ISchedule object.
create(String) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
create(InputStream) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
create(String) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
create(InputStream) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
create(String) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl
create(InputStream) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl
create(TokenizerFactory) - Static method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory: Create an API wrapped schedule from a given ISchedule object.
create(IUpdater) - Static method in class weka.dl4j.updater.Updater: Create an API wrapped updater from a given updater object.
create(IWeightNoise) - Static method in class weka.dl4j.weightnoise.AbstractWeightNoise: Create an API wrapped updater from a given updater object.
createDataset() - Method in class weka.core.converters.ImageDirectoryLoader: Main entrypoint.
createGradient(Color, Color, int) - Static method in class weka.dl4j.interpretability.Gradient: Creates an array of Color objects for use as a gradient, using a linear interpolation between the two specified colors.
createMultiGradient(Color[], int) - Static method in class weka.dl4j.interpretability.Gradient: Creates an array of Color objects for use as a gradient, using an array of Color objects.
Cropping2D - Class in weka.dl4j.layers: A version of DeepLearning4j's DenseLayer that implements WEKA option handling.
Cropping2D() - Constructor for class weka.dl4j.layers.Cropping2D: Constructor for setting some defaults.
CustomBroadcast - Class in weka.dl4j.layers.lambda: Required for loading the EfficientNet family of models.
CustomBroadcast() - Constructor for class weka.dl4j.layers.lambda.CustomBroadcast: Instantiate the layer.
CustomBroadcast(long) - Constructor for class weka.dl4j.layers.lambda.CustomBroadcast: Instantiate the layer with the supplied width.
CustomModelSetup - Class in weka.dl4j.inference: Config class to hold parameters for a custom model that was trained previously.
CustomModelSetup() - Constructor for class weka.dl4j.inference.CustomModelSetup
CustomNet - Class in weka.dl4j.zoo: A dummy ZooModel which is empty.
CustomNet() - Constructor for class weka.dl4j.zoo.CustomNet

D

decodeCNNShape(int[]) - Static method in class weka.dl4j.Utils: Decode a CNN Input shape.
decodeCNNShape(long[]) - Static method in class weka.dl4j.Utils: Decode a CNN Input shape.
decodePredictions(INDArray) - Method in class weka.dl4j.inference.ModelOutputDecoder: Decode predictions, without any image or model name.
decodePredictions(INDArray, String, String) - Method in class weka.dl4j.inference.ModelOutputDecoder: Main entrypoint - decode the model predictions, saving the image and model name alongside it.
DefaultDataSetIterator - Class in weka.dl4j.iterators.dataset: An nd4j mini-batch iterator that iterates a given dataset.
DefaultDataSetIterator(DataSet, int) - Constructor for class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Constructs a new dataset iterator.
defaultFileLocation() - Static method in class weka.dl4j.Utils: The default location for a file parameter.
DefaultInstanceIterator - Class in weka.dl4j.iterators.instance: Converts the given Instances object into a DataSet and then constructs and returns a DefaultDataSetIterator.
DefaultInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.DefaultInstanceIterator
DefaultStepFunction - Class in weka.dl4j.stepfunctions: A version of DeepLearning4j's DefaultStepFunction that implements WEKA option handling.
DefaultStepFunction() - Constructor for class weka.dl4j.stepfunctions.DefaultStepFunction
DefaultTokenizerFactory - Class in weka.dl4j.text.tokenization.tokenizer.factory: A wrapper that extends the TokenizerFactory API for DefaultTokenizerFactoryImpl.
DefaultTokenizerFactory() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory
DefaultTokenizerFactoryImpl - Class in weka.dl4j.text.tokenization.tokenizer.factory.impl: A serializable version of DeepLearning4j's DefaultTokenizerFactory.
DefaultTokenizerFactoryImpl() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.impl.DefaultTokenizerFactoryImpl
defineLayer(SameDiff, SDVariable) - Method in class weka.dl4j.layers.lambda.CustomBroadcast
DenseLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's DenseLayer that implements WEKA option handling.
DenseLayer() - Constructor for class weka.dl4j.layers.DenseLayer: Constructor for setting some defaults.
DenseNet - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of DenseNet.
DenseNet() - Constructor for class weka.dl4j.zoo.keras.DenseNet: Instantiate the model.
DenseNet.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
DepthwiseConvolution2DLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's DepthwiseConvolution2DLayer that implements WEKA option handling.
DepthwiseConvolution2DLayer() - Constructor for class weka.dl4j.layers.DepthwiseConvolution2DLayer: Constructor for setting some defaults.
Disabled - Class in weka.dl4j.distribution: Disabled Distribution.
Disabled() - Constructor for class weka.dl4j.distribution.Disabled
Disabled - Class in weka.dl4j.dropout: Disabled dropout.
Disabled() - Constructor for class weka.dl4j.dropout.Disabled
Disabled - Class in weka.dl4j.weightnoise: Disabled option for WeightNoise.
Disabled() - Constructor for class weka.dl4j.weightnoise.Disabled
Distribution<T extends org.deeplearning4j.nn.conf.distribution.Distribution> - Class in weka.dl4j.distribution: Abstract distribution class.
Distribution() - Constructor for class weka.dl4j.distribution.Distribution
distributionForInstance(Instance) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: The method to use when making a prediction for a test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.RnnSequenceClassifier
distributionsForInstances(Instances) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: The method to use when making predictions for test instances.
distributionsForInstances(Instances) - Method in class weka.classifiers.functions.RnnSequenceClassifier: The method to use when making predictions for test instances.
Dl4jAbstractStopwords - Class in weka.dl4j.text.stopwords: Abstract stopwords handler for DL4j.
Dl4jAbstractStopwords() - Constructor for class weka.dl4j.text.stopwords.Dl4jAbstractStopwords
Dl4jAlexNet - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's LeNet ZooModel.
Dl4jAlexNet() - Constructor for class weka.dl4j.zoo.Dl4jAlexNet: Instantiate the model.
Dl4jCNNExplorer - Class in weka.dl4j.inference: Tool to allow easy experimentation and exploration of a trained ComputationGraph - either from a previously trained Dl4jMlpClassifier, or from a pretrained Zoo Model (default).
Dl4jCNNExplorer() - Constructor for class weka.dl4j.inference.Dl4jCNNExplorer
Dl4jDarknet19 - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's Darknet19 ZooModel.
Dl4jDarknet19() - Constructor for class weka.dl4j.zoo.Dl4jDarknet19: Instantiate the model.
Dl4jDarknet19.VARIATION - Enum in weka.dl4j.zoo: Variations of the model.
Dl4jFaceNetNN4Small2 - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's FaceNetNN4Small2 ZooModel.
Dl4jFaceNetNN4Small2() - Constructor for class weka.dl4j.zoo.Dl4jFaceNetNN4Small2: Instantiate the model.
Dl4jInceptionResNetV1 - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's InceptionResNetV1 ZooModel.
Dl4jInceptionResNetV1() - Constructor for class weka.dl4j.zoo.Dl4jInceptionResNetV1: Instantiate the model.
Dl4jLeNet - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's LeNet ZooModel.
Dl4jLeNet() - Constructor for class weka.dl4j.zoo.Dl4jLeNet: Instantiate the model.
Dl4jMlpClassifier - Class in weka.classifiers.functions: A wrapper for DeepLearning4j that can be used to train a multi-layer perceptron.
Dl4jMlpClassifier() - Constructor for class weka.classifiers.functions.Dl4jMlpClassifier: Instantiate the model.
Dl4jMlpFilter - Class in weka.filters.unsupervised.attribute: Weka filter that uses a neural network trained via Dl4jMlpClassifier as feature transformation.
Dl4jMlpFilter() - Constructor for class weka.filters.unsupervised.attribute.Dl4jMlpFilter: FILTER CODE.
Dl4jNASNet - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's NASNet ZooModel.
Dl4jNASNet() - Constructor for class weka.dl4j.zoo.Dl4jNASNet
Dl4jNull - Class in weka.dl4j.text.stopwords: Dummy stopwords scheme, returns an empty list of stopWords..
Dl4jNull() - Constructor for class weka.dl4j.text.stopwords.Dl4jNull
Dl4jRainbow - Class in weka.dl4j.text.stopwords: *
Dl4jRainbow() - Constructor for class weka.dl4j.text.stopwords.Dl4jRainbow
Dl4jResNet50 - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's ResNet50 ZooModel.
Dl4jResNet50() - Constructor for class weka.dl4j.zoo.Dl4jResNet50: Instantiate the model.
Dl4jSimpleCNN - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's SimpleCNN ZooModel.
Dl4jSimpleCNN() - Constructor for class weka.dl4j.zoo.Dl4jSimpleCNN
Dl4jSqueezeNet - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's ResNet50 ZooModel.
Dl4jSqueezeNet() - Constructor for class weka.dl4j.zoo.Dl4jSqueezeNet: Instantiate the model.
Dl4jStringToGlove - Class in weka.filters.unsupervised.attribute: An attribute filter that calculates word embeddings on a String attribute using the Glove implementation provided by DeepLearning4j.
Dl4jStringToGlove() - Constructor for class weka.filters.unsupervised.attribute.Dl4jStringToGlove
Dl4jStringToWord2Vec - Class in weka.filters.unsupervised.attribute: An attribute filter that calculates word embeddings on a String attribute using the Word2vec implementation provided by DeepLearning4j.
Dl4jStringToWord2Vec() - Constructor for class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
Dl4jStringToWordEmbeddings - Class in weka.filters.unsupervised.attribute: An abstract attribute filter that calculates word embeddings on a String attribute.
Dl4jStringToWordEmbeddings() - Constructor for class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
Dl4jVGG - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's VGG16 ZooModel.
Dl4jVGG() - Constructor for class weka.dl4j.zoo.Dl4jVGG: Instantiate the model.
Dl4jWordsFromFile - Class in weka.dl4j.text.stopwords
Dl4jWordsFromFile() - Constructor for class weka.dl4j.text.stopwords.Dl4jWordsFromFile
Dl4jXception - Class in weka.dl4j.zoo: A WEKA version of DeepLearning4j's XCeption ZooModel.
Dl4jXception() - Constructor for class weka.dl4j.zoo.Dl4jXception: Instantiate the model.
done() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Clean up after learning.
DropConnect - Class in weka.dl4j.weightnoise: DropConnect wrapper.
DropConnect() - Constructor for class weka.dl4j.weightnoise.DropConnect
Dropout - Class in weka.dl4j.dropout
Dropout() - Constructor for class weka.dl4j.dropout.Dropout
DropoutLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's DropoutLayer that implements WEKA option handling.
DropoutLayer() - Constructor for class weka.dl4j.layers.DropoutLayer: Constructor for setting some defaults.

E

EarlyStopping - Class in weka.dl4j.earlystopping: Early stopping implementation to stop training after N epochs without loss improvement on a separate validation set.
EarlyStopping() - Constructor for class weka.dl4j.earlystopping.EarlyStopping
EarlyStopping(int, double) - Constructor for class weka.dl4j.earlystopping.EarlyStopping: Constructor setting maxEpochsNoImprovement and validation split
EfficientNet - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of EfficientNet.
EfficientNet() - Constructor for class weka.dl4j.zoo.keras.EfficientNet: Instantiate the model.
EfficientNet.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
EmptyIteratorException - Exception in weka.core: Exception raised when the iterator was unexpectedly empty
EmptyIteratorException(String) - Constructor for exception weka.core.EmptyIteratorException
EmptyIteratorException(String, Throwable) - Constructor for exception weka.core.EmptyIteratorException
EndingPreProcessor - Class in weka.dl4j.text.tokenization.preprocessor: A wrapper that extends the PreProcessor API for EndingPreProcessorImpl.
EndingPreProcessor() - Constructor for class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor
EndingPreProcessorImpl - Class in weka.dl4j.text.tokenization.preprocessor.impl: A serializable version of DeepLearning4j's EndingPreProcessor.
EndingPreProcessorImpl() - Constructor for class weka.dl4j.text.tokenization.preprocessor.impl.EndingPreProcessorImpl
enforceValidForZooModel(AbstractZooModel) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator: The only one-channel zoo model currently implemented is Dl4JLeNet.
enforceZooModelSize(AbstractZooModel) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Enforces the input image size if using a zoo model.
EpochListener - Class in weka.dl4j.listener: A listener that prints the model score every epoch.
EpochListener() - Constructor for class weka.dl4j.listener.EpochListener
evaluate(ComputationGraph) - Method in class weka.dl4j.earlystopping.EarlyStopping: Evaluate a model and check if the training should continue.
ExplorerDl4jInference - Class in weka.gui.explorer: Explorer panel for the Dl4j Model Inference Window
ExplorerDl4jInference() - Constructor for class weka.gui.explorer.ExplorerDl4jInference: Create the panel.
ExponentialSchedule - Class in weka.dl4j.schedules: Exponential schedule for learning rates.
ExponentialSchedule() - Constructor for class weka.dl4j.schedules.ExponentialSchedule

F

featurizeForLayer(String, DataSetIterator, PoolingType) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Uses the DL4J TransferLearningHelper to featurize the instances using activations from the given layer
FeedForwardLayer<T extends org.deeplearning4j.nn.conf.layers.FeedForwardLayer> - Class in weka.dl4j.layers: Abstract feed forward layer.
FeedForwardLayer() - Constructor for class weka.dl4j.layers.FeedForwardLayer
FILE_EXTENSION - Static variable in class weka.core.converters.Word2VecLoader: the file extension.
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.Word2VecLoader: the extension for compressed files.
FileLabeledSentenceProvider - Class in weka.dl4j.iterators.provider: Implement LabeledSentenceProvider for loading labeled files.
FileLabeledSentenceProvider(List<File>, List<String>, int) - Constructor for class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
fileListForFolder(File) - Method in class weka.core.converters.ImageDirectoryLoader: Appends the folder that the image is in, to the image path.
FILTER_NONE - Static variable in class weka.classifiers.functions.Dl4jMlpClassifier: filter: No normalization/standardization.
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.Dl4jMlpClassifier: filter: Normalize training data.
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.Dl4jMlpClassifier: filter: Standardize training data.
finish() - Method in class weka.core.progress.AbstractProgressBar: Perform any teardown (e.g., close popup window, display completion message)
finish() - Method in class weka.core.progress.CommandLineProgressBar: Perform any teardown (e.g., close popup window, display completion message)
finish() - Method in class weka.core.progress.GUIProgressBar: Perform any teardown (e.g., close popup window, display completion message)
finish() - Method in class weka.core.progress.ProgressManager: Close out the progress bar.
finishProgress() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Close up all progress managers when we finish processing.
fromBackend(ConvolutionLayer.AlgoMode) - Static method in enum weka.dl4j.enums.AlgoMode: Parse backend algo mode and return weka enum implementation.
fromBackend(ConvolutionMode) - Static method in enum weka.dl4j.enums.ConvolutionMode: Parse backend convolution mode and return weka enum implementation.
fromBackend(GradientNormalization) - Static method in enum weka.dl4j.enums.GradientNormalization: Parse backend gradient normalization and return weka enum implementation.
fromBackend(PoolingType) - Static method in enum weka.dl4j.enums.PoolingType: Parse backend pooling type and return weka enum implementation.
fromBackend(PretrainedType) - Static method in enum weka.dl4j.enums.PretrainedType: Parse backend pooling type and return weka enum implementation.
fromBackend(ScheduleType) - Static method in enum weka.dl4j.schedules.ScheduleType: Parse backend schedule type and return weka enum implementation.

G

GaussianDropout - Class in weka.dl4j.dropout: Gaussian dropout implementation.
GaussianDropout() - Constructor for class weka.dl4j.dropout.GaussianDropout
GaussianNoise - Class in weka.dl4j.dropout: Gaussian noise implementation.
GaussianNoise() - Constructor for class weka.dl4j.dropout.GaussianNoise
generateAndSaveOutputMap() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Generate the output heatmap, and save to file.
generateHeatmapToImage(int[], String[], boolean) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator: Generates heatmaps for the supplied classes, returning a human-viewable heatmap summary.
generateHeatmapToImage() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Generates heatmaps, returning a human-viewable heatmap summary.
generateHeatmapToImage(int[], String[], boolean) - Method in class weka.dl4j.interpretability.ScoreCAM
generateHeatmapToImage() - Method in class weka.dl4j.interpretability.WekaScoreCAM
generateOutputMap() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Generate and return the heatmap.
getAction() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getActivationFunction() - Method in class weka.dl4j.layers.ActivationLayer
getActivationFunction() - Method in class weka.dl4j.layers.FeedForwardLayer
getActivationsAtLayers(String[], Instances) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Overridden method - if no pooling type is given then set it to NONE Uses the given set of layers to extract features for the given dataset
getActivationsAtLayers(String[], Instances, PoolingType) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Uses the given set of layers to extract features for the given dataset
getAlpha() - Method in class weka.dl4j.activations.ActivationELU
getAlpha() - Method in class weka.dl4j.activations.ActivationLReLU
getAlpha() - Method in class weka.dl4j.dropout.AlphaDropout
getAlpha() - Method in class weka.dl4j.layers.CenterLossOutputLayer
getApplicationName() - Method in class weka.dl4j.IsGPUAvailable
getAttributeName(Map<String, Long>, int) - Static method in class weka.dl4j.Utils: Helper function for getting the new layer name when using the Dl4jMlpFilter The attributes are named after the layer they originated from, so this function counts throught the attributes per layer, comparing it with the given index to determine a) which layer the activation came from and b) which number activation this is.
getBackend() - Method in class weka.dl4j.activations.Activation
getBackend() - Method in class weka.dl4j.activations.ActivationELU
getBackend() - Method in class weka.dl4j.activations.ActivationLReLU
getBackend() - Method in interface weka.dl4j.ApiWrapper: Access the DL4J backend.
getBackend() - Method in class weka.dl4j.distribution.BinomialDistribution
getBackend() - Method in class weka.dl4j.distribution.Distribution
getBackend() - Method in class weka.dl4j.dropout.AbstractDropout
getBackend() - Method in class weka.dl4j.dropout.AlphaDropout
getBackend() - Method in class weka.dl4j.dropout.GaussianDropout
getBackend() - Method in class weka.dl4j.dropout.GaussianNoise
getBackend() - Method in enum weka.dl4j.enums.AlgoMode
getBackend() - Method in enum weka.dl4j.enums.ConvolutionMode
getBackend() - Method in enum weka.dl4j.enums.GradientNormalization
getBackend() - Method in enum weka.dl4j.enums.PoolingType
getBackend() - Method in enum weka.dl4j.enums.PretrainedType
getBackend() - Method in class weka.dl4j.layers.BroadcastLambdaLayer
getBackend() - Method in class weka.dl4j.layers.Layer
getBackend() - Method in class weka.dl4j.lossfunctions.LossFunction
getBackend() - Method in class weka.dl4j.schedules.ConstantSchedule
getBackend() - Method in class weka.dl4j.schedules.InverseSchedule
getBackend() - Method in class weka.dl4j.schedules.Schedule
getBackend() - Method in enum weka.dl4j.schedules.ScheduleType
getBackend() - Method in class weka.dl4j.stepfunctions.StepFunction
getBackend() - Method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess
getBackend() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory
getBackend() - Method in class weka.dl4j.updater.Adam
getBackend() - Method in class weka.dl4j.updater.Updater
getBackend() - Method in class weka.dl4j.weightnoise.AbstractWeightNoise
getBatchSize() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getBatchSize() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getBatchSize() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getBeta() - Method in class weka.dl4j.layers.BatchNormalization
getBeta1() - Method in class weka.dl4j.updater.Adam
getBeta1() - Method in class weka.dl4j.updater.AdaMax
getBeta1() - Method in class weka.dl4j.updater.Nadam
getBeta2() - Method in class weka.dl4j.updater.Adam
getBeta2() - Method in class weka.dl4j.updater.AdaMax
getBeta2() - Method in class weka.dl4j.updater.Nadam
getBiasInit() - Method in class weka.dl4j.NeuralNetConfiguration
getBiasUpdater() - Method in class weka.dl4j.NeuralNetConfiguration
getBuiltInClassMap() - Method in class weka.dl4j.inference.ModelOutputDecoder
getCacheMode() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getCapabilities() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.RnnSequenceClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getChannelsLast() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
getChannelsLast() - Method in class weka.dl4j.zoo.AbstractZooModel
getClasses() - Method in class weka.dl4j.inference.ModelOutputDecoder: Parses the classmap file into a String[]
getClassID() - Method in class weka.dl4j.inference.Prediction
getClassID() - Method in class weka.dl4j.inference.PredictionClass
getClassMap() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getClassMapFile() - Method in class weka.dl4j.inference.ModelOutputDecoder
getClassName() - Method in class weka.dl4j.inference.Prediction
getClassName() - Method in class weka.dl4j.inference.PredictionClass
getClassProbability() - Method in class weka.dl4j.inference.Prediction
getComputationGraph() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getConcat_words() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getConcatWords() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getConvolutionMode() - Method in class weka.dl4j.layers.ConvolutionLayer
getConvolutionMode() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer
getConvolutionMode() - Method in class weka.dl4j.layers.SubsamplingLayer
getCudnnAlgoMode() - Method in class weka.dl4j.layers.ConvolutionLayer
getCudnnAlgoMode() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer
getCurrentClassMap() - Method in class weka.gui.explorer.SaliencyMapWindow
getCurrentPredictions() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getCursor() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getCustomModelSetup() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getCustomModelSetup() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getDataSet() - Method in class weka.core.converters.ImageDirectoryLoader
getDataSet() - Method in class weka.core.converters.Word2VecLoader
getDataSetIterator(Instances, int) - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Returns the actual iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Returns the actual iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator: Returns the actual iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator: Returns the actual iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: This method returns the iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator: Returns the actual iterator.
getDataSetIterator(Instances, int, int) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
getDataSetPreProcessor() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getDecay() - Method in class weka.dl4j.layers.BatchNormalization
getDecayRate() - Method in class weka.dl4j.schedules.StepSchedule
getDefaultClassID() - Method in class weka.gui.explorer.SaliencyMapWindow
getDefaultGraph() - Method in class weka.dl4j.zoo.AbstractZooModel: Convenience method to returns a default pretrained graph for this zoo model
getDelimiters() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
getDelimiters() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
getDist() - Method in class weka.dl4j.NeuralNetConfiguration
getDistribution() - Method in class weka.dl4j.weightnoise.WeightNoise
getDl4jLogLevel() - Method in class weka.core.LogConfiguration: Get the Dl4j log level.
getDl4jMlpClassifier() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getDoNotClearFilesystemCache() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getDropout() - Method in class weka.dl4j.layers.DropoutLayer
getDropout() - Method in class weka.dl4j.NeuralNetConfiguration
getEarlyStopping() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getEmbedding_prefix() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getEpochs() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getEps() - Method in class weka.dl4j.layers.BatchNormalization
getEps() - Method in class weka.dl4j.layers.SubsamplingLayer
getEpsilon() - Method in class weka.dl4j.updater.AdaDelta
getEpsilon() - Method in class weka.dl4j.updater.AdaGrad
getEpsilon() - Method in class weka.dl4j.updater.Adam
getEpsilon() - Method in class weka.dl4j.updater.AdaMax
getEpsilon() - Method in class weka.dl4j.updater.Nadam
getEpsilon() - Method in class weka.dl4j.updater.RmsProp
getETAString() - Method in class weka.core.progress.AbstractProgressBar: Gets the estimated time remaining of the task, or "" if indeterminate
getExplorer() - Method in class weka.gui.explorer.ExplorerDl4jInference: returns the parent Explorer frame
getExtraLayersToRemove() - Method in class weka.dl4j.zoo.AbstractZooModel
getFeatureExtractionLayer() - Method in class weka.dl4j.zoo.AbstractZooModel
getFieldValue(Object, String) - Static method in class weka.dl4j.Utils: Access private field of a given object.
getFileDescription() - Method in class weka.core.converters.Word2VecLoader
getFileExtension() - Method in class weka.core.converters.Word2VecLoader
getFileExtensions() - Method in class weka.core.converters.Word2VecLoader
getFilterType() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getGain() - Method in class weka.dl4j.distribution.OrthogonalDistribution
getGamma() - Method in class weka.dl4j.layers.BatchNormalization
getGamma() - Method in class weka.dl4j.schedules.ExponentialSchedule
getGamma() - Method in class weka.dl4j.schedules.InverseSchedule
getGamma() - Method in class weka.dl4j.schedules.SigmoidSchedule
getGateActivationFn() - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.
getGateActivationFn() - Method in class weka.dl4j.layers.LSTM
getGenerateSaliencyMap() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getGradientCheck() - Method in class weka.dl4j.layers.CenterLossOutputLayer
getGradientNormalization() - Method in class weka.dl4j.NeuralNetConfiguration
getGradientNormalizationThreshold() - Method in class weka.dl4j.NeuralNetConfiguration
getHeight() - Method in interface weka.dl4j.iterators.instance.api.ConvolutionalIterator
getHeight() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
getHeight() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
getHeight() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getImageInstanceIterator() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getImagePreProcessingScaler() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.AbstractZooModel: Get the preprocessor to process this model's data with
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.CustomNet: By default, training a model uses the below scaler for the Dl4jMlpClassifier.
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jAlexNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jDarknet19
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jFaceNetNN4Small2
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jInceptionResNetV1
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jLeNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jResNet50
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jSqueezeNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jVGG
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.Dl4jXception
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasDenseNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasEfficientNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasInceptionV3
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasNASNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasResNet
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasVGG
getImagePreprocessingScaler() - Method in class weka.dl4j.zoo.KerasXception
getImagesLocation() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
getImagesLocation() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getImplementingWrapper(Class<T>, V, String) - Static method in class weka.dl4j.ApiWrapperUtil: Return the implementing wrapper class of a given backend object.
getInitialValue() - Method in class weka.dl4j.schedules.ConstantSchedule
getInitialValue() - Method in class weka.dl4j.schedules.MapSchedule: Deprecated.
getInitialValue() - Method in class weka.dl4j.schedules.Schedule
getInputChannels() - Method in class weka.dl4j.inference.CustomModelSetup
getInputDirectory() - Method in class weka.core.converters.ImageDirectoryLoader
getInputFilename() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getInputHeight() - Method in class weka.dl4j.inference.CustomModelSetup
getInputShape(CustomModelSetup) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getInputShape() - Method in class weka.dl4j.zoo.AbstractZooModel: Get the input shape of this zoomodel
getInputShape() - Method in class weka.dl4j.zoo.CustomNet
getInputShape() - Method in class weka.dl4j.zoo.Dl4jAlexNet
getInputShape() - Method in class weka.dl4j.zoo.Dl4jDarknet19
getInputShape() - Method in class weka.dl4j.zoo.Dl4jFaceNetNN4Small2
getInputShape() - Method in class weka.dl4j.zoo.Dl4jInceptionResNetV1
getInputShape() - Method in class weka.dl4j.zoo.Dl4jLeNet
getInputShape() - Method in class weka.dl4j.zoo.Dl4jResNet50
getInputShape() - Method in class weka.dl4j.zoo.Dl4jSqueezeNet
getInputShape() - Method in class weka.dl4j.zoo.Dl4jVGG
getInputShape() - Method in class weka.dl4j.zoo.Dl4jXception
getInputShape() - Method in class weka.dl4j.zoo.KerasDenseNet
getInputShape() - Method in class weka.dl4j.zoo.KerasEfficientNet
getInputShape() - Method in class weka.dl4j.zoo.KerasInceptionV3
getInputShape() - Method in class weka.dl4j.zoo.KerasNASNet
getInputShape() - Method in class weka.dl4j.zoo.KerasResNet
getInputShape() - Method in class weka.dl4j.zoo.KerasVGG
getInputShape() - Method in class weka.dl4j.zoo.KerasXception
getInputWidth() - Method in class weka.dl4j.inference.CustomModelSetup
getInstanceIterator() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getInstanceIterator() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
getIsMinibatch() - Method in class weka.dl4j.layers.BatchNormalization
getIterationListener() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getIterations() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getKernelSize() - Method in class weka.dl4j.layers.ConvolutionLayer
getKernelSize() - Method in class weka.dl4j.layers.SubsamplingLayer
getKernelSizeX() - Method in class weka.dl4j.layers.ConvolutionLayer
getKernelSizeX() - Method in class weka.dl4j.layers.SubsamplingLayer
getKernelSizeY() - Method in class weka.dl4j.layers.ConvolutionLayer
getKernelSizeY() - Method in class weka.dl4j.layers.SubsamplingLayer
getL1() - Method in class weka.dl4j.NeuralNetConfiguration
getL2() - Method in class weka.dl4j.NeuralNetConfiguration
getLabelForPath(String) - Method in class weka.dl4j.ArffMetaDataLabelGenerator: Select the label based on the path in the metadata
getLabelForPath(URI) - Method in class weka.dl4j.ArffMetaDataLabelGenerator
getLabels() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Gets the labels.
getLabels() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
getLabels() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
getLambda() - Method in class weka.dl4j.dropout.AlphaDropout
getLambda() - Method in class weka.dl4j.layers.CenterLossOutputLayer
getLayerName() - Method in class weka.dl4j.layers.Layer
getLayers() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getLayerSize() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getLearningRate() - Method in class weka.dl4j.updater.AdaDelta
getLearningRate() - Method in class weka.dl4j.updater.Updater: Get the learning rate
getLearningRate() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getLearningRateSchedule() - Method in class weka.dl4j.updater.Updater: Get the learning rate schedule
getLevel() - Method in enum weka.core.LogConfiguration.LogLevel: Get the internal log level.
getLoadLayerSpecification() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getLockGammaAndBeta() - Method in class weka.dl4j.layers.BatchNormalization
getLogConfig() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Get the log configuration.
getLogFile() - Method in class weka.core.LogConfiguration: Get the log file
getLossFn() - Method in class weka.dl4j.layers.CenterLossOutputLayer
getLossFn() - Method in class weka.dl4j.layers.LossLayer
getLossFn() - Method in class weka.dl4j.layers.OutputLayer
getLossFn() - Method in class weka.dl4j.layers.RnnOutputLayer
getLower() - Method in class weka.dl4j.distribution.UniformDistribution
getLowerBound() - Method in class weka.dl4j.activations.ActivationRReLU
getMatchingClasses(String) - Method in class weka.gui.explorer.ClassSelector: Get the list of classes in our classmap that matches the supplied pattern.
getMaxEpochsNoImprovement() - Method in class weka.dl4j.earlystopping.EarlyStopping
getMaxIter() - Method in class weka.dl4j.schedules.PolySchedule
getMaxProgress() - Method in class weka.core.progress.AbstractProgressBar: Get the max progress value
getMaxSentenceLength() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getMean() - Method in class weka.dl4j.distribution.LogNormalDistribution
getMean() - Method in class weka.dl4j.distribution.NormalDistribution
getMean() - Method in class weka.dl4j.distribution.TruncatedNormalDistribution
getMenuBar() - Method in class weka.dl4j.IsGPUAvailable
getMenuEntryText() - Method in class weka.dl4j.IsGPUAvailable
getMenuToDisplayIn() - Method in class weka.dl4j.IsGPUAvailable
getMinLearningRate() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getMinWordFrequency() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getModel() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Get the ComputationGraph model
getModelInputShape() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getModelInputShape() - Method in class weka.dl4j.interpretability.ScoreCAM
getModelName() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Get the name of the loaded model
getModelName() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Get the name of the loaded model
getModelName() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
getModelOutputDecoder() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getMomentum() - Method in class weka.dl4j.updater.Nesterovs
getN() - Method in class weka.dl4j.inference.TopNPredictions
getN() - Method in class weka.dl4j.listener.EpochListener
getNd4jLogLevel() - Method in class weka.core.LogConfiguration: Get the Nd4j log level.
getNegative() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getNeuralNetConfiguration() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getNext(DataSetIterator) - Static method in class weka.dl4j.Utils: Fix for issue with JVM crashing https://github.com/eclipse/deeplearning4j/issues/8976#issuecomment-639946904 It is recommended to use this helper function in WekaDeeplearning4j rather than using iter.next() directly.
getNext(DataSetIterator, int) - Static method in class weka.dl4j.Utils: Fix for issue with JVM crashing https://github.com/eclipse/deeplearning4j/issues/8976#issuecomment-639946904 It is recommended to use this helper function in WekaDeeplearning4j rather than using iter.next() directly.
getNextInstance(Instances) - Method in class weka.core.converters.ImageDirectoryLoader
getNextInstance(Instances) - Method in class weka.core.converters.Word2VecLoader
getNextWekaString() - Method in class weka.dl4j.text.sentenceiterator.WekaInstanceSentenceIterator: Gets the next String from a Weka Instance
getNMax() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
getNMax() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
getNMax() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
getNMax() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
getNMin() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
getNMin() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
getNMin() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
getNMin() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
getNormalizeHeatmap() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getNOut() - Method in class weka.dl4j.layers.BatchNormalization: Deprecated.
getNOut() - Method in class weka.dl4j.layers.ConvolutionLayer
getNOut() - Method in class weka.dl4j.layers.FeedForwardLayer
getNumberOfTrials() - Method in class weka.dl4j.distribution.BinomialDistribution
getNumChannels() - Method in interface weka.dl4j.iterators.instance.api.ConvolutionalIterator
getNumChannels() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
getNumChannels() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
getNumChannels() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getNumClasses() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getNumEpochs() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getNumFExtractOutputs() - Method in class weka.dl4j.zoo.AbstractZooModel
getNumGPUs() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getOptimizationAlgo() - Method in class weka.dl4j.NeuralNetConfiguration
getOptions() - Method in class weka.core.converters.ImageDirectoryLoader: Gets the current settings of the Classifier.
getOptions() - Method in class weka.core.LogConfiguration: Gets the current settings of the log configuration
getOptions() - Method in class weka.dl4j.activations.Activation: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationCube: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationELU: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationHardSigmoid: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationHardTanH: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationIdentity: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationLReLU: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationRationalTanh: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationReLU: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationRReLU: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationSigmoid: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationSoftmax: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationSoftPlus: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationSoftSign: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationSwish: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.activations.ActivationTanH: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.BinomialDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.ConstantDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.Distribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.LogNormalDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.NormalDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.OrthogonalDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.TruncatedNormalDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.distribution.UniformDistribution: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.dropout.AbstractDropout: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.dropout.AlphaDropout: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.dropout.Dropout: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.dropout.GaussianDropout: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.dropout.GaussianNoise: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.earlystopping.EarlyStopping: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.inference.CustomModelSetup: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.inference.ModelOutputDecoder: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.IsGPUAvailable: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.ActivationLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.BatchNormalization: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.BroadcastLambdaLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.CenterLossOutputLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.ConvolutionLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.Cropping2D: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.DenseLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.DropoutLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.FeedForwardLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.GlobalPoolingLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.

Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.Layer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.LocalResponseNormalization: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.LossLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.LSTM: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.NoParamLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.OutputLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.RnnOutputLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.SameDiffLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.SeperableConvolution2DLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.SubsamplingLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.layers.ZeroPaddingLayer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.listener.TrainingListener: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossBinaryXENT: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossCosineProximity: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossFMeasure: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossHinge: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossKLD: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossL1: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossL2: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMAE: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMAPE: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMCXENT: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMixtureDensity: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMSE: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMSLE: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossMultiLabel: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossNegativeLogLikelihood: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossPoisson: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.lossfunctions.LossSquaredHinge: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.NeuralNetConfiguration: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.ConstantSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.ExponentialSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.InverseSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.MapSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.PolySchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.Schedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.SigmoidSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.schedules.StepSchedule: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.stepfunctions.DefaultStepFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.stepfunctions.GradientStepFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.stepfunctions.NegativeDefaultStepFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.stepfunctions.NegativeGradientStepFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.stepfunctions.StepFunction: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.AdaDelta: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.AdaGrad: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.Adam: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.AdaMax: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.Nadam: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.Nesterovs: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.RmsProp: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.Sgd: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.updater.Updater: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.weightnoise.AbstractWeightNoise: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.weightnoise.DropConnect: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.weightnoise.WeightNoise: Gets the current settings of the Classifier.
getOptions() - Method in class weka.dl4j.zoo.AbstractZooModel: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getOutputFile() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getOutputFileName() - Method in class weka.core.converters.ImageDirectoryLoader
getOutputlayer() - Method in class weka.dl4j.zoo.AbstractZooModel
getOutputType(int, InputType) - Method in class weka.dl4j.layers.lambda.CustomBroadcast
getP() - Method in class weka.dl4j.dropout.AlphaDropout
getP() - Method in class weka.dl4j.dropout.Dropout: Get the learning rate schedule
getPadding() - Method in class weka.dl4j.layers.ConvolutionLayer
getPadding() - Method in class weka.dl4j.layers.SubsamplingLayer
getPadding() - Method in class weka.dl4j.layers.ZeroPaddingLayer
getPaddingColumns() - Method in class weka.dl4j.layers.ConvolutionLayer
getPaddingColumns() - Method in class weka.dl4j.layers.SubsamplingLayer
getPaddingColumns() - Method in class weka.dl4j.layers.ZeroPaddingLayer
getPaddingRows() - Method in class weka.dl4j.layers.ConvolutionLayer
getPaddingRows() - Method in class weka.dl4j.layers.SubsamplingLayer
getPaddingRows() - Method in class weka.dl4j.layers.ZeroPaddingLayer
getParameterAveragingFrequency() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getPathURIs() - Method in class weka.dl4j.ArffMetaDataLabelGenerator: Get all paths as uris
getPnorm() - Method in class weka.dl4j.layers.GlobalPoolingLayer
getPnorm() - Method in class weka.dl4j.layers.SubsamplingLayer
getPoolingDimensions() - Method in class weka.dl4j.layers.GlobalPoolingLayer
getPoolingType() - Method in class weka.dl4j.layers.GlobalPoolingLayer
getPoolingType() - Method in class weka.dl4j.layers.SubsamplingLayer
getPoolingType() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
getPower() - Method in class weka.dl4j.schedules.InverseSchedule
getPower() - Method in class weka.dl4j.schedules.PolySchedule
getPrediction(int) - Method in class weka.dl4j.inference.TopNPredictions: Get the prediction at index i.
getPredictionClass() - Method in class weka.dl4j.inference.Prediction
getPrefetchBufferSize() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getPreProcessor() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Gets the preprocessor.
getPreProcessor() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
getPreProcessor() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
getPreProcessor() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getPretrainedType() - Method in class weka.dl4j.zoo.AbstractZooModel
getPrettyName() - Method in class weka.dl4j.zoo.AbstractZooModel
getProbabilityOfSuccess() - Method in class weka.dl4j.distribution.BinomialDistribution
getProgressManager() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getProgressMessage() - Method in class weka.core.progress.AbstractProgressBar: Return the user supplied progress message
getpSchedule() - Method in class weka.dl4j.dropout.AlphaDropout
getpSchedule() - Method in class weka.dl4j.dropout.Dropout
getQueueSize() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
getRateSchedule() - Method in class weka.dl4j.dropout.GaussianDropout
getRateSchedule() - Method in class weka.dl4j.dropout.GaussianNoise
getRelationalAttributeIndex() - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
GetResolvedPath(String) - Method in class weka.dl4j.ResourceResolver
getResume() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Returns true if the model is to be finalized (or has been finalized) after training.
getRevision() - Method in class weka.core.converters.ImageDirectoryLoader
getRevision() - Method in class weka.core.converters.Word2VecLoader
getRho() - Method in class weka.dl4j.updater.AdaDelta
getRmsDecay() - Method in class weka.dl4j.updater.RmsProp
getSaliencyMapWrapper() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getSampling() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
getScheduleType() - Method in class weka.dl4j.schedules.Schedule
getSeed() - Method in class weka.dl4j.NeuralNetConfiguration
getSeed() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getSentenceProvider() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getSentenceProvider(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator: Create a sentence provider from the given data.
getSentenceProvider(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
getSentenceProvider(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
getSerializedModelFile() - Method in class weka.dl4j.inference.CustomModelSetup
getSerializedModelFile() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: GET/SET METHODS
getStd() - Method in class weka.dl4j.distribution.LogNormalDistribution
getStd() - Method in class weka.dl4j.distribution.NormalDistribution
getStd() - Method in class weka.dl4j.distribution.TruncatedNormalDistribution
getStdDev() - Method in class weka.dl4j.dropout.GaussianNoise
getStemmer() - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl
getStemmer() - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor
getStep() - Method in class weka.dl4j.schedules.StepSchedule
getStepSize() - Method in class weka.dl4j.schedules.SigmoidSchedule
getStopList() - Method in class weka.dl4j.text.stopwords.Dl4jAbstractStopwords: Returns the list of stopwords.
getStopList() - Method in class weka.dl4j.text.stopwords.Dl4jNull
getStopList() - Method in class weka.dl4j.text.stopwords.Dl4jRainbow
getStopList() - Method in class weka.dl4j.text.stopwords.Dl4jWordsFromFile
getStopwords() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getStopwords() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getStopWordsHandler() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getStride() - Method in class weka.dl4j.layers.ConvolutionLayer
getStride() - Method in class weka.dl4j.layers.SubsamplingLayer
getStrideColumns() - Method in class weka.dl4j.layers.ConvolutionLayer
getStrideColumns() - Method in class weka.dl4j.layers.SubsamplingLayer
getStrideRows() - Method in class weka.dl4j.layers.ConvolutionLayer
getStrideRows() - Method in class weka.dl4j.layers.SubsamplingLayer
getStructure() - Method in class weka.core.converters.ImageDirectoryLoader
getStructure() - Method in class weka.core.converters.Word2VecLoader
getTabTitle() - Method in class weka.gui.explorer.ExplorerDl4jInference: Returns the title for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.ExplorerDl4jInference: Returns the tooltip for the tab in the Explorer
getTargetClass() - Method in class weka.gui.explorer.ClassSelector
getTargetClassIDs() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
getTargetClassIDsAsInt() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
gettBPTTbackwardLength() - Method in class weka.classifiers.functions.RnnSequenceClassifier
gettBPTTforwardLength() - Method in class weka.classifiers.functions.RnnSequenceClassifier
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTextIndex() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getTextsLocation() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
getTextsLocation() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
getTokenizerFactory() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getTokenizerFactory() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getTokenPreProcess() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getTokenPreProcessor() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
getTokenPreProcessor() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
getTokenPreProcessor() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl
getTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer
getTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer
getTopPrediction() - Method in class weka.dl4j.inference.TopNPredictions
getTopPredictions() - Method in class weka.dl4j.inference.TopNPredictions
getTrainBatchSize() - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Getting the training batch size
getTrainBatchSize() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getTransformationLayer(int) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
getTransformationLayers() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
getTruncateLength() - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
getTruncateLength() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getUnknown() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getUnknownWordHandling() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getUnknownWordSentinel() - Static method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getUpdater() - Method in class weka.dl4j.NeuralNetConfiguration
getUpper() - Method in class weka.dl4j.distribution.UniformDistribution
getUpperBound() - Method in class weka.dl4j.activations.ActivationRReLU
getUseCustomModel() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getUseDefaultFeatureLayer() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
getUseNormalizedWordVectors() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getValDataSetIterator() - Method in class weka.dl4j.earlystopping.EarlyStopping: Get the validation dataset iterator
getValidationSetPercentage() - Method in class weka.dl4j.earlystopping.EarlyStopping
getValue() - Method in class weka.dl4j.distribution.ConstantDistribution
getValues() - Method in class weka.dl4j.schedules.MapSchedule
getVariation() - Method in class weka.dl4j.zoo.AbstractZooModel: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.CustomNet: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jAlexNet: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jDarknet19
getVariation() - Method in class weka.dl4j.zoo.Dl4jFaceNetNN4Small2: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jInceptionResNetV1: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jLeNet: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jResNet50: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jSqueezeNet: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.Dl4jVGG
getVariation() - Method in class weka.dl4j.zoo.Dl4jXception: Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
getVariation() - Method in class weka.dl4j.zoo.KerasDenseNet
getVariation() - Method in class weka.dl4j.zoo.KerasEfficientNet
getVariation() - Method in class weka.dl4j.zoo.KerasInceptionV3
getVariation() - Method in class weka.dl4j.zoo.KerasNASNet
getVariation() - Method in class weka.dl4j.zoo.KerasResNet
getVariation() - Method in class weka.dl4j.zoo.KerasVGG
getVariation() - Method in class weka.dl4j.zoo.KerasXception
getWeightInit() - Method in class weka.dl4j.NeuralNetConfiguration
getWeightNoise() - Method in class weka.dl4j.NeuralNetConfiguration
getWeightRetainProbability() - Method in class weka.dl4j.weightnoise.DropConnect: Get the learning rate schedule
getWeightRetainProbabilitySchedule() - Method in class weka.dl4j.weightnoise.DropConnect: Get the learning rate schedule
getWekaDl4jLogLevel() - Method in class weka.core.LogConfiguration: Get the WekaDeeplearning4j log level.
getWidth() - Method in interface weka.dl4j.iterators.instance.api.ConvolutionalIterator
getWidth() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
getWidth() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
getWidth() - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
getWindowSize() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getWordVectorLocation() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getWordVectors() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getWordVectors() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
getWordVectorSize() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
getWorkers() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
getZooModel() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Get the modelzoo model
getZooModel() - Method in class weka.classifiers.functions.RnnSequenceClassifier: Deprecated.
getZooModelType() - Method in class weka.dl4j.inference.Dl4jCNNExplorer
getZooModelType() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
globalInfo() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: .
globalInfo() - Method in class weka.classifiers.functions.RnnSequenceClassifier
globalInfo() - Method in class weka.dl4j.earlystopping.EarlyStopping: Returns a string describing this search method
globalInfo() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
globalInfo() - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator
globalInfo() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Return the global info for this class.
globalInfo() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
globalInfo() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator
globalInfo() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
globalInfo() - Method in class weka.dl4j.layers.ActivationLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.BatchNormalization: Global info.
globalInfo() - Method in class weka.dl4j.layers.BroadcastLambdaLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.CenterLossOutputLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.ConvolutionLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.Cropping2D: Global info.
globalInfo() - Method in class weka.dl4j.layers.DenseLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.DropoutLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.GlobalPoolingLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.

Global info.
globalInfo() - Method in class weka.dl4j.layers.LocalResponseNormalization: Global info.
globalInfo() - Method in class weka.dl4j.layers.LossLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.LSTM: Global info.
globalInfo() - Method in class weka.dl4j.layers.OutputLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.RnnOutputLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.SeperableConvolution2DLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.SubsamplingLayer: Global info.
globalInfo() - Method in class weka.dl4j.layers.ZeroPaddingLayer: Global info.
globalInfo() - Method in class weka.dl4j.listener.EpochListener: Returns a string describing this search method
globalInfo() - Method in class weka.dl4j.NeuralNetConfiguration: Returns a string describing this search method
globalInfo() - Method in class weka.dl4j.text.stopwords.Dl4jNull: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.dl4j.text.stopwords.Dl4jRainbow: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.dl4j.text.stopwords.Dl4jWordsFromFile: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory: Returns a string describing this object.
globalInfo() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory: Returns a string describing this object.
globalInfo() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec: Returns a string describing this filter.
GlobalPoolingLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's GlobalPooling that implements WEKA option handling.
GlobalPoolingLayer() - Constructor for class weka.dl4j.layers.GlobalPoolingLayer: Constructor for setting some defaults.
Gradient - Class in weka.dl4j.interpretability: There are a number of defined gradient types (look at the static fields), but you can create any gradient you like by using either of the following functions: public static Color[] createMultiGradient(Color[] colors, int numSteps) public static Color[] createGradient(Color one, Color two, int numSteps) You can then assign an arbitrary Color[] object to the HeatMap as follows:
Gradient() - Constructor for class weka.dl4j.interpretability.Gradient
GRADIENT_ALPHA - Static variable in class weka.dl4j.interpretability.Gradient
GRADIENT_BLACK_TO_WHITE - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient from black (low) to white (high)
GRADIENT_BLUE_TO_RED - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient from blue (low) to red (high)
GRADIENT_GREEN_YELLOW_ORANGE_RED - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient through green, yellow, orange, red
GRADIENT_HEAT - Static variable in class weka.dl4j.interpretability.Gradient: Produces a different gradient for hot things (black, brown, orange, white)
GRADIENT_HOT - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient for hot things (black, red, orange, yellow, white)
GRADIENT_MAROON_TO_GOLD - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient using the University of Minnesota's school colors, from maroon (low) to gold (high)
GRADIENT_PLASMA - Static variable in class weka.dl4j.interpretability.Gradient: From https://revolution-computing.typepad.com/.a/6a010534b1db25970b01bb0931cd68970d-pi
GRADIENT_RAINBOW - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient through the rainbow: violet, blue, green, yellow, orange, red
GRADIENT_RED_TO_GREEN - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient from red (low) to green (high)
GRADIENT_ROY - Static variable in class weka.dl4j.interpretability.Gradient: Produces a gradient through red, orange, yellow
GradientNormalization - Enum in weka.dl4j.enums: Proxy Enum for GradientNormalization.
GradientStepFunction - Class in weka.dl4j.stepfunctions: A version of DeepLearning4j's GradientStepFunction that implements WEKA option handling.
GradientStepFunction() - Constructor for class weka.dl4j.stepfunctions.GradientStepFunction
GravesLSTM - Class in weka.dl4j.layers: Deprecated.
GravesLSTM() - Constructor for class weka.dl4j.layers.GravesLSTM: Deprecated.

Constructor for setting some defaults.
GUIProgressBar - Class in weka.core.progress: Progress bar panel displayed in the GUI.
GUIProgressBar(double, String) - Constructor for class weka.core.progress.GUIProgressBar: Init the GUI progress bar

H

hasLearningRate() - Method in class weka.dl4j.updater.AdaDelta
hasLearningRate() - Method in class weka.dl4j.updater.AdaGrad
hasLearningRate() - Method in class weka.dl4j.updater.Updater
hasMoreTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer
hasMoreTokens() - Method in class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer
hasNext() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Whether another batch of data is still available.
hasNext() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
hasNext() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
hasNext() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
hasNext() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
hasNext() - Method in class weka.dl4j.text.sentenceiterator.WekaInstanceSentenceIterator

I

IMAGE_FILE_EXTENSIONS - Static variable in class weka.gui.explorer.ExplorerDl4jInference: Allowable image file extensions.
ImageDirectoryLoader - Class in weka.core.converters: Loader for image datasets that are in a folder-organized fashion i.e., image class for an instance is inferred from the folder name it resides in.
ImageDirectoryLoader() - Constructor for class weka.core.converters.ImageDirectoryLoader
imageFromINDArray(INDArray) - Method in class weka.dl4j.interpretability.ScoreCAM: Takes an INDArray containing an image loaded using the native image loader libraries associated with DL4J, and converts it into a BufferedImage.
ImageInstanceIterator - Class in weka.dl4j.iterators.instance: An iterator that loads images.
ImageInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.ImageInstanceIterator
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Performs efficient batch prediction
InceptionResNetV2 - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of InceptionResNetV2.
InceptionResNetV2() - Constructor for class weka.dl4j.zoo.keras.InceptionResNetV2: Instantiate the model.
InceptionResNetV2.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
InceptionV3 - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of InceptionV3.
InceptionV3() - Constructor for class weka.dl4j.zoo.keras.InceptionV3: Instantiate the model.
InceptionV3.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
increment() - Method in class weka.core.progress.AbstractProgressBar: Helper methods so consumers don't need to keep track of iterations.
increment() - Method in class weka.core.progress.ProgressManager: Increment the progress bar.
inference() - Static method in class weka.examples.WekaDeeplearning4jExamples
inferLabelClasses() - Method in class weka.dl4j.ArffMetaDataLabelGenerator
init(DataSetIterator) - Method in class weka.dl4j.earlystopping.EarlyStopping: Initialize the underlying dl4j EarlyStopping object
init() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Initialize the ComputationGraph.
init(int, int, int, int, DataSetIterator, DataSetIterator) - Method in class weka.dl4j.listener.TrainingListener: Initialize the iterator with its necessary member variables
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.AbstractZooModel: Initialize the ZooModel as MLP.
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.CustomNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jAlexNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jDarknet19
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jFaceNetNN4Small2
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jInceptionResNetV1
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jLeNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jResNet50
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jSqueezeNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jVGG
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.Dl4jXception
init() - Method in class weka.dl4j.zoo.keras.KerasZooModel
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasDenseNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasEfficientNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasInceptionV3
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasNASNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasResNet
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasVGG
init(int, long, int[], boolean) - Method in class weka.dl4j.zoo.KerasXception
initialize() - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Initialize the iterator
initialize() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
initialize() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator
initialize() - Method in class weka.dl4j.text.stopwords.Dl4jAbstractStopwords: initializes the dictionary
initialize() - Method in class weka.dl4j.text.stopwords.Dl4jNull
initialize() - Method in class weka.dl4j.text.stopwords.Dl4jRainbow: Performs intialization of the scheme.
initialize() - Method in class weka.dl4j.text.stopwords.Dl4jWordsFromFile: Performs intialization of the scheme.
initializeBackend() - Method in class weka.dl4j.activations.ActivationCube
initializeBackend() - Method in class weka.dl4j.activations.ActivationELU
initializeBackend() - Method in class weka.dl4j.activations.ActivationHardSigmoid
initializeBackend() - Method in class weka.dl4j.activations.ActivationHardTanH
initializeBackend() - Method in class weka.dl4j.activations.ActivationIdentity
initializeBackend() - Method in class weka.dl4j.activations.ActivationLReLU
initializeBackend() - Method in class weka.dl4j.activations.ActivationRationalTanh
initializeBackend() - Method in class weka.dl4j.activations.ActivationReLU
initializeBackend() - Method in class weka.dl4j.activations.ActivationRReLU
initializeBackend() - Method in class weka.dl4j.activations.ActivationSigmoid
initializeBackend() - Method in class weka.dl4j.activations.ActivationSoftmax
initializeBackend() - Method in class weka.dl4j.activations.ActivationSoftPlus
initializeBackend() - Method in class weka.dl4j.activations.ActivationSoftSign
initializeBackend() - Method in class weka.dl4j.activations.ActivationSwish
initializeBackend() - Method in class weka.dl4j.activations.ActivationTanH
initializeBackend() - Method in interface weka.dl4j.ApiWrapper: Initialize the DL4J backend.
initializeBackend() - Method in class weka.dl4j.distribution.BinomialDistribution
initializeBackend() - Method in class weka.dl4j.distribution.ConstantDistribution
initializeBackend() - Method in class weka.dl4j.distribution.Disabled
initializeBackend() - Method in class weka.dl4j.distribution.LogNormalDistribution
initializeBackend() - Method in class weka.dl4j.distribution.NormalDistribution
initializeBackend() - Method in class weka.dl4j.distribution.OrthogonalDistribution
initializeBackend() - Method in class weka.dl4j.distribution.TruncatedNormalDistribution
initializeBackend() - Method in class weka.dl4j.distribution.UniformDistribution
initializeBackend() - Method in class weka.dl4j.dropout.AlphaDropout
initializeBackend() - Method in class weka.dl4j.dropout.Disabled
initializeBackend() - Method in class weka.dl4j.dropout.Dropout
initializeBackend() - Method in class weka.dl4j.dropout.GaussianDropout
initializeBackend() - Method in class weka.dl4j.dropout.GaussianNoise
initializeBackend() - Method in enum weka.dl4j.enums.AlgoMode
initializeBackend() - Method in enum weka.dl4j.enums.ConvolutionMode
initializeBackend() - Method in enum weka.dl4j.enums.GradientNormalization
initializeBackend() - Method in enum weka.dl4j.enums.PoolingType
initializeBackend() - Method in enum weka.dl4j.enums.PretrainedType
initializeBackend() - Method in class weka.dl4j.layers.ActivationLayer
initializeBackend() - Method in class weka.dl4j.layers.BatchNormalization
initializeBackend() - Method in class weka.dl4j.layers.BroadcastLambdaLayer
initializeBackend() - Method in class weka.dl4j.layers.CenterLossOutputLayer
initializeBackend() - Method in class weka.dl4j.layers.ConvolutionLayer
initializeBackend() - Method in class weka.dl4j.layers.Cropping2D
initializeBackend() - Method in class weka.dl4j.layers.DenseLayer
initializeBackend() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer
initializeBackend() - Method in class weka.dl4j.layers.DropoutLayer
initializeBackend() - Method in class weka.dl4j.layers.GlobalPoolingLayer
initializeBackend() - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.
initializeBackend() - Method in class weka.dl4j.layers.LocalResponseNormalization
initializeBackend() - Method in class weka.dl4j.layers.LossLayer
initializeBackend() - Method in class weka.dl4j.layers.LSTM
initializeBackend() - Method in class weka.dl4j.layers.OutputLayer
initializeBackend() - Method in class weka.dl4j.layers.RnnOutputLayer
initializeBackend() - Method in class weka.dl4j.layers.SeperableConvolution2DLayer
initializeBackend() - Method in class weka.dl4j.layers.SubsamplingLayer
initializeBackend() - Method in class weka.dl4j.layers.ZeroPaddingLayer
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossBinaryXENT
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossCosineProximity
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossFMeasure
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossHinge
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossKLD
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossL1
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossL2
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMAPE
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMCXENT
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMixtureDensity
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMSE
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMSLE
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossMultiLabel
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossNegativeLogLikelihood
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossPoisson
initializeBackend() - Method in class weka.dl4j.lossfunctions.LossSquaredHinge
initializeBackend() - Method in class weka.dl4j.schedules.ConstantSchedule
initializeBackend() - Method in class weka.dl4j.schedules.ExponentialSchedule
initializeBackend() - Method in class weka.dl4j.schedules.InverseSchedule
initializeBackend() - Method in class weka.dl4j.schedules.MapSchedule
initializeBackend() - Method in class weka.dl4j.schedules.PolySchedule
initializeBackend() - Method in enum weka.dl4j.schedules.ScheduleType
initializeBackend() - Method in class weka.dl4j.schedules.SigmoidSchedule
initializeBackend() - Method in class weka.dl4j.schedules.StepSchedule
initializeBackend() - Method in class weka.dl4j.stepfunctions.DefaultStepFunction
initializeBackend() - Method in class weka.dl4j.stepfunctions.GradientStepFunction
initializeBackend() - Method in class weka.dl4j.stepfunctions.NegativeDefaultStepFunction
initializeBackend() - Method in class weka.dl4j.stepfunctions.NegativeGradientStepFunction
initializeBackend() - Method in class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor
initializeBackend() - Method in class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor
initializeBackend() - Method in class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor
initializeBackend() - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor
initializeBackend() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
initializeBackend() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory
initializeBackend() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
initializeBackend() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory
initializeBackend() - Method in class weka.dl4j.updater.AdaDelta
initializeBackend() - Method in class weka.dl4j.updater.AdaGrad
initializeBackend() - Method in class weka.dl4j.updater.Adam
initializeBackend() - Method in class weka.dl4j.updater.AdaMax
initializeBackend() - Method in class weka.dl4j.updater.Nadam
initializeBackend() - Method in class weka.dl4j.updater.Nesterovs
initializeBackend() - Method in class weka.dl4j.updater.NoOp
initializeBackend() - Method in class weka.dl4j.updater.RmsProp
initializeBackend() - Method in class weka.dl4j.updater.Sgd
initializeBackend() - Method in class weka.dl4j.weightnoise.Disabled
initializeBackend() - Method in class weka.dl4j.weightnoise.DropConnect
initializeBackend() - Method in class weka.dl4j.weightnoise.WeightNoise
initializeClassifier(Instances) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: The method used to initialize the classifier.
initializeClassifier(Instances) - Method in class weka.classifiers.functions.RnnSequenceClassifier: The method used to initialize the classifier.
initOnGUI(int, int) - Method in class weka.gui.explorer.ClassSelector: Init the GUI elements.
initPretrained(PretrainedType) - Method in class weka.dl4j.zoo.keras.KerasZooModel
initWordVectors() - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator: Initialize the word vectors from the given file
initZooModel(ZooModel, ComputationGraph, long, int, boolean) - Method in class weka.dl4j.zoo.AbstractZooModel: Initialize the zoo model with the supplied params.
inputColumns() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Returns the number of input columns.
inputColumns() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
inputColumns() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
inputShape - Static variable in class weka.dl4j.zoo.keras.DenseNet: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.EfficientNet: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.InceptionResNetV2: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.InceptionV3: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.MobileNet: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.NASNet: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.ResNet: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.VGG: Default input shape of the model.
inputShape - Static variable in class weka.dl4j.zoo.keras.Xception: Default input shape of the model.
instancesToConvDataSet(Instances, int, int, int) - Static method in class weka.dl4j.Utils: Converts a set of training instances to a DataSet prepared for the convolution operation using the height, width and number of channels.
instancesToDataSet(Instances) - Static method in class weka.dl4j.Utils: Converts a set of training instances to a DataSet.
InvalidInputDataException - Exception in weka.core: Exception raised in the case of an invalid input data
InvalidInputDataException(String) - Constructor for exception weka.core.InvalidInputDataException
InvalidInputDataException(String, Throwable) - Constructor for exception weka.core.InvalidInputDataException
InvalidLayerConfigurationException - Exception in weka.core: Exception raised when the the configuration is invalid.
InvalidLayerConfigurationException(String, Layer) - Constructor for exception weka.core.InvalidLayerConfigurationException
InvalidLayerConfigurationException(String, Layer, Throwable) - Constructor for exception weka.core.InvalidLayerConfigurationException
InvalidNetworkArchitectureException - Exception in weka.core: Exception raised when the the network architecture is invalid.
InvalidNetworkArchitectureException(String) - Constructor for exception weka.core.InvalidNetworkArchitectureException
InvalidNetworkArchitectureException(String, Throwable) - Constructor for exception weka.core.InvalidNetworkArchitectureException
InvalidValidationPercentageException - Exception in weka.core: Exception raised in the case of a validation percentage which might be too low / too high
InvalidValidationPercentageException(String) - Constructor for exception weka.core.InvalidValidationPercentageException
InvalidValidationPercentageException(String, Throwable) - Constructor for exception weka.core.InvalidValidationPercentageException
InverseSchedule - Class in weka.dl4j.schedules: Inverse exponential schedule for learning rates.
InverseSchedule() - Constructor for class weka.dl4j.schedules.InverseSchedule
invokeMethod(Object, String, Object...) - Static method in class weka.dl4j.Utils: Invoke a method on a given object.
isAdditive() - Method in class weka.dl4j.weightnoise.WeightNoise
isAllowParallelTokenization() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
isAppend() - Method in class weka.core.LogConfiguration
isApplyToBias() - Method in class weka.dl4j.weightnoise.WeightNoise
isChannelsLast(INDArray) - Static method in class weka.dl4j.Utils: Shape will either be something like [1, 56, 56, 128] or [1, 128, 56, 56] If it's the former then return true.
isCollapseDimensions() - Method in class weka.dl4j.layers.GlobalPoolingLayer
isCustom() - Method in enum weka.dl4j.enums.PoolingType: NONE and MIN are not DL4J pooling types, only used for pooling activations
isEnableScavenger() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
isFilterMode() - Method in class weka.classifiers.functions.Dl4jMlpClassifier
IsGPUAvailable - Class in weka.dl4j
IsGPUAvailable() - Constructor for class weka.dl4j.IsGPUAvailable
isImage(String) - Method in class weka.core.converters.ImageDirectoryLoader: Check whether the supplied path is a valid image.
isImageChannelsLast() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
isIndeterminate() - Method in class weka.core.progress.AbstractProgressBar: Gets the indeterminate status of the progress bar
isIntermediateEvaluationsEnabled() - Method in class weka.dl4j.listener.EpochListener
isLockGammaBeta() - Method in class weka.dl4j.layers.BatchNormalization
isMetaArff(Instances) - Static method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Are the input instances from a 'meta' arff (just points to the image location)
isMiniBatch() - Method in class weka.dl4j.NeuralNetConfiguration
isMinimize() - Method in class weka.dl4j.NeuralNetConfiguration
isPretrained() - Method in class weka.dl4j.zoo.AbstractZooModel
isRequiresPooling() - Method in class weka.dl4j.zoo.AbstractZooModel
isSentencesAlongHeight() - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
isUseAdaGrad() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
isUseHierarchicSoftmax() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
isValidOutputLayer(boolean, Layer) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: Checks if the layer is a valid output layer
iterationDone(Model, int, int) - Method in class weka.dl4j.listener.TrainingListener
iterationIncremented() - Method in interface weka.dl4j.interpretability.listeners.IterationIncrementListener: Called when iterations incremented.
IterationIncrementListener - Interface in weka.dl4j.interpretability.listeners: Event listener for when iterations increment.
iterationsFinished() - Method in interface weka.dl4j.interpretability.listeners.IterationsFinishedListener: Called when iterations finish.
IterationsFinishedListener - Interface in weka.dl4j.interpretability.listeners: Event listener for when iterations finish.
iterationsStarted(int) - Method in interface weka.dl4j.interpretability.listeners.IterationsStartedListener: Called when iterations start.
IterationsStartedListener - Interface in weka.dl4j.interpretability.listeners: Event listener for when iterations increment.

K

KerasConstants - Class in weka.dl4j.zoo.keras: Simple class to hold URLs and checksums of all Keras models in WDL4J.
KerasConstants() - Constructor for class weka.dl4j.zoo.keras.KerasConstants
KerasDenseNet - Class in weka.dl4j.zoo: Wrapper class for Keras version of DenseNet.
KerasDenseNet() - Constructor for class weka.dl4j.zoo.KerasDenseNet: Instantiate the model.
KerasEfficientNet - Class in weka.dl4j.zoo: Wrapper class for Keras version of EfficientNet.
KerasEfficientNet() - Constructor for class weka.dl4j.zoo.KerasEfficientNet: Instantiate the model.
KerasInceptionResNetV2 - Class in weka.dl4j.zoo
KerasInceptionResNetV2() - Constructor for class weka.dl4j.zoo.KerasInceptionResNetV2
KerasInceptionV3 - Class in weka.dl4j.zoo: Wrapper class for Keras version of InceptionV3.
KerasInceptionV3() - Constructor for class weka.dl4j.zoo.KerasInceptionV3: Instantiate the model.
KerasMobileNet - Class in weka.dl4j.zoo
KerasMobileNet() - Constructor for class weka.dl4j.zoo.KerasMobileNet
KerasModelConverter - Class in weka.dl4j.scripts.keras_downloading: This class loads in a folder of Keras files, and one by one converts them into the native DL4J format (.zip).
KerasModelConverter() - Constructor for class weka.dl4j.scripts.keras_downloading.KerasModelConverter
KerasNASNet - Class in weka.dl4j.zoo: Wrapper class for Keras version of NASNet.
KerasNASNet() - Constructor for class weka.dl4j.zoo.KerasNASNet: Instantiate the model.
KerasResNet - Class in weka.dl4j.zoo: Wrapper class for Keras version of ResNet.
KerasResNet() - Constructor for class weka.dl4j.zoo.KerasResNet: Instantiate the model.
KerasVGG - Class in weka.dl4j.zoo: Wrapper class for Keras version of VGG.
KerasVGG() - Constructor for class weka.dl4j.zoo.KerasVGG: Instantiate the model.
KerasXception - Class in weka.dl4j.zoo: Wrapper class for Keras version of Xception.
KerasXception() - Constructor for class weka.dl4j.zoo.KerasXception: Instantiate the model.
KerasZooModel - Class in weka.dl4j.zoo.keras: This class essentially copies DL4J's ZooModel class, allowing the custom Keras models to provide the same interface as those models provided by DL4J.
KerasZooModel() - Constructor for class weka.dl4j.zoo.keras.KerasZooModel

L

Layer<T extends org.deeplearning4j.nn.conf.layers.Layer> - Class in weka.dl4j.layers: Abstract layer class.
Layer() - Constructor for class weka.dl4j.layers.Layer
listOptions() - Method in class weka.core.converters.ImageDirectoryLoader: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.LogConfiguration: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.Activation: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationCube: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationELU: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationHardSigmoid: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationHardTanH: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationIdentity: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationLReLU: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationRationalTanh: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationReLU: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationRReLU: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationSigmoid: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationSoftmax: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationSoftPlus: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationSoftSign: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationSwish: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.activations.ActivationTanH: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.BinomialDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.ConstantDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.Distribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.LogNormalDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.NormalDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.OrthogonalDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.TruncatedNormalDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.distribution.UniformDistribution: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.dropout.AbstractDropout: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.dropout.AlphaDropout: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.dropout.Dropout: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.dropout.GaussianDropout: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.dropout.GaussianNoise: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.earlystopping.EarlyStopping: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.inference.CustomModelSetup: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.inference.ModelOutputDecoder: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.IsGPUAvailable: Returns an enumeration of all the available options..
listOptions() - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.ActivationLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.BatchNormalization: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.BroadcastLambdaLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.CenterLossOutputLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.ConvolutionLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.Cropping2D: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.DenseLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.DropoutLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.FeedForwardLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.GlobalPoolingLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.

Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.Layer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.LocalResponseNormalization: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.LossLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.LSTM: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.NoParamLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.OutputLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.RnnOutputLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.SameDiffLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.SeperableConvolution2DLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.SubsamplingLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.layers.ZeroPaddingLayer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.listener.TrainingListener: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossBinaryXENT: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossCosineProximity: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossFMeasure: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossHinge: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossKLD: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossL1: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossL2: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMAE: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMAPE: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMCXENT: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMixtureDensity: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMSE: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMSLE: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossMultiLabel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossNegativeLogLikelihood: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossPoisson: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.lossfunctions.LossSquaredHinge: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.NeuralNetConfiguration: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.ConstantSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.ExponentialSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.InverseSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.MapSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.PolySchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.Schedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.SigmoidSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.schedules.StepSchedule: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.stepfunctions.DefaultStepFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.stepfunctions.GradientStepFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.stepfunctions.NegativeDefaultStepFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.stepfunctions.NegativeGradientStepFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.stepfunctions.StepFunction: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.AdaDelta: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.AdaGrad: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.Adam: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.AdaMax: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.Nadam: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.Nesterovs: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.RmsProp: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.Sgd: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.updater.Updater: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.weightnoise.AbstractWeightNoise: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.weightnoise.DropConnect: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.weightnoise.WeightNoise: Returns an enumeration describing the available options.
listOptions() - Method in class weka.dl4j.zoo.AbstractZooModel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
listOptions() - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
loadInferenceModel(File, AbstractZooModel) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: Load a Dl4jMlpClassifier for use in the Inference Panel - no need to supply Instances or InstanceIterators
loadModel(Instances, File, AbstractZooModel, AbstractInstanceIterator) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: Load a Dl4jMlpClassifier for use with the given instances and iterator
loadZooModelNoData(int, long, int[]) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Load a ComputationGraph without any data - used in the Dl4j Inference panel
LocalResponseNormalization - Class in weka.dl4j.layers: A version of DeepLearning4j's LocalResponseNormalization layer that implements WEKA option handling.
LocalResponseNormalization() - Constructor for class weka.dl4j.layers.LocalResponseNormalization: Constructor for setting some defaults.
Locations - Static variable in class weka.dl4j.zoo.keras.KerasConstants: URLs of model files.
log(String) - Method in class weka.dl4j.listener.EpochListener
log(String) - Method in class weka.dl4j.listener.TrainingListener: Log a message
LogConfiguration - Class in weka.core: General logger configuration.
LogConfiguration() - Constructor for class weka.core.LogConfiguration
LogConfiguration.LogLevel - Enum in weka.core: Available log levels.
LogNormalDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's LogNormalDistribution that implements WEKA option handling.
LogNormalDistribution() - Constructor for class weka.dl4j.distribution.LogNormalDistribution
LossBinaryXENT - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossBinaryXENT that implements WEKA option handling.
LossBinaryXENT() - Constructor for class weka.dl4j.lossfunctions.LossBinaryXENT
LossCosineProximity - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossCosineProximity that implements WEKA option handling.
LossCosineProximity() - Constructor for class weka.dl4j.lossfunctions.LossCosineProximity
LossFMeasure - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossFMeasure that implements WEKA option handling.
LossFMeasure() - Constructor for class weka.dl4j.lossfunctions.LossFMeasure
LossFunction<T extends org.nd4j.linalg.lossfunctions.ILossFunction> - Class in weka.dl4j.lossfunctions
LossFunction() - Constructor for class weka.dl4j.lossfunctions.LossFunction
LossHinge - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossHinge that implements WEKA option handling.
LossHinge() - Constructor for class weka.dl4j.lossfunctions.LossHinge
LossKLD - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossKLD that implements WEKA option handling.
LossKLD() - Constructor for class weka.dl4j.lossfunctions.LossKLD
LossL1 - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossL1 that implements WEKA option handling.
LossL1() - Constructor for class weka.dl4j.lossfunctions.LossL1
LossL2 - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossL2 that implements WEKA option handling.
LossL2() - Constructor for class weka.dl4j.lossfunctions.LossL2
LossLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's LossLayer layer that implements WEKA option handling.
LossLayer() - Constructor for class weka.dl4j.layers.LossLayer: Constructor for setting some defaults.
LossMAE - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMAE that implements WEKA option handling.
LossMAE() - Constructor for class weka.dl4j.lossfunctions.LossMAE
LossMAPE - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMAPE that implements WEKA option handling.
LossMAPE() - Constructor for class weka.dl4j.lossfunctions.LossMAPE
LossMCXENT - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMCXENT that implements WEKA option handling.
LossMCXENT() - Constructor for class weka.dl4j.lossfunctions.LossMCXENT
LossMixtureDensity - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMixtureDensity that implements WEKA option handling.
LossMixtureDensity() - Constructor for class weka.dl4j.lossfunctions.LossMixtureDensity
LossMSE - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMSE that implements WEKA option handling.
LossMSE() - Constructor for class weka.dl4j.lossfunctions.LossMSE
LossMSLE - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMSLE that implements WEKA option handling.
LossMSLE() - Constructor for class weka.dl4j.lossfunctions.LossMSLE
LossMultiLabel - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossMultiLabel that implements WEKA option handling.
LossMultiLabel() - Constructor for class weka.dl4j.lossfunctions.LossMultiLabel
LossNegativeLogLikelihood - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossNegativeLogLikelihood that implements WEKA option handling.
LossNegativeLogLikelihood() - Constructor for class weka.dl4j.lossfunctions.LossNegativeLogLikelihood
LossPoisson - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossPoisson that implements WEKA option handling.
LossPoisson() - Constructor for class weka.dl4j.lossfunctions.LossPoisson
LossSquaredHinge - Class in weka.dl4j.lossfunctions: A version of DeepLearning4j's LossSquaredHinge that implements WEKA option handling.
LossSquaredHinge() - Constructor for class weka.dl4j.lossfunctions.LossSquaredHinge
LowCasePreProcessor - Class in weka.dl4j.text.tokenization.preprocessor: A wrapper that extends the PreProcessor API for LowCasePreProcessorImpl.
LowCasePreProcessor() - Constructor for class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor
LowCasePreProcessorImpl - Class in weka.dl4j.text.tokenization.preprocessor.impl: A serializable version of DeepLearning4j's LowCasePreProcessor.
LowCasePreProcessorImpl() - Constructor for class weka.dl4j.text.tokenization.preprocessor.impl.LowCasePreProcessorImpl
LSTM - Class in weka.dl4j.layers: A version of DeepLearning4j's LSTM layer that implements WEKA option handling.
LSTM() - Constructor for class weka.dl4j.layers.LSTM: Constructor for setting some defaults.

M

main(String[]) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: The main method for running this class.
main(String[]) - Static method in class weka.core.converters.ImageDirectoryLoader: Main entrypoint if invoking class independently
main(String[]) - Static method in class weka.core.converters.Word2VecLoader: Main method for testing this class.
main(String[]) - Static method in class weka.dl4j.scripts.keras_downloading.KerasModelConverter: Main entrypoint.
main(String[]) - Static method in class weka.examples.WekaDeeplearning4jExamples
MapSchedule - Class in weka.dl4j.schedules: Map schedule for learning rates.
MapSchedule() - Constructor for class weka.dl4j.schedules.MapSchedule
metaData() - Method in class weka.dl4j.zoo.keras.KerasZooModel
MissingOutputLayerException - Exception in weka.core: Exception raised in the case of a missing output layer as last layer
MissingOutputLayerException(String) - Constructor for exception weka.core.MissingOutputLayerException
MissingOutputLayerException(String, Throwable) - Constructor for exception weka.core.MissingOutputLayerException
MobileNet - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of MobileNet.
MobileNet() - Constructor for class weka.dl4j.zoo.keras.MobileNet: Instantiate the model.
MobileNet.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ExplorerDl4jInference: The filename extension that should be used for model files.
modelFamily() - Method in class weka.dl4j.zoo.keras.DenseNet
modelFamily() - Method in class weka.dl4j.zoo.keras.EfficientNet
modelFamily() - Method in class weka.dl4j.zoo.keras.InceptionResNetV2
modelFamily() - Method in class weka.dl4j.zoo.keras.InceptionV3
modelFamily() - Method in class weka.dl4j.zoo.keras.KerasZooModel: Get the model family.
modelFamily() - Method in class weka.dl4j.zoo.keras.MobileNet
modelFamily() - Method in class weka.dl4j.zoo.keras.NASNet
modelFamily() - Method in class weka.dl4j.zoo.keras.ResNet
modelFamily() - Method in class weka.dl4j.zoo.keras.VGG
modelFamily() - Method in class weka.dl4j.zoo.keras.Xception
ModelOutputDecoder - Class in weka.dl4j.inference: Decodes model outputs into a human-readable and more workable format.
ModelOutputDecoder() - Constructor for class weka.dl4j.inference.ModelOutputDecoder
modelPrettyName() - Method in class weka.dl4j.zoo.keras.DenseNet
modelPrettyName() - Method in class weka.dl4j.zoo.keras.EfficientNet
modelPrettyName() - Method in class weka.dl4j.zoo.keras.InceptionResNetV2
modelPrettyName() - Method in class weka.dl4j.zoo.keras.InceptionV3
modelPrettyName() - Method in class weka.dl4j.zoo.keras.KerasZooModel: Get the pretty name of the model (e.g., ResNet 50)
modelPrettyName() - Method in class weka.dl4j.zoo.keras.MobileNet
modelPrettyName() - Method in class weka.dl4j.zoo.keras.NASNet
modelPrettyName() - Method in class weka.dl4j.zoo.keras.ResNet
modelPrettyName() - Method in class weka.dl4j.zoo.keras.VGG
modelPrettyName() - Method in class weka.dl4j.zoo.keras.Xception
modelType() - Method in class weka.dl4j.zoo.keras.KerasZooModel

N

Nadam - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's Nadam.
Nadam() - Constructor for class weka.dl4j.updater.Nadam
NASNet - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of NASNet.
NASNet() - Constructor for class weka.dl4j.zoo.keras.NASNet: Instantiate the model.
NASNet.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
ndArrayToInstances(INDArray, Instances, Map<String, Long>) - Static method in class weka.dl4j.Utils: Convert an arbitrary NDArray to Weka instances.
needsReshaping(INDArray) - Static method in class weka.dl4j.Utils: Determines if the activations need reshaping.
NegativeDefaultStepFunction - Class in weka.dl4j.stepfunctions: A version of DeepLearning4j's NegativeDefaultStepFunction that implements WEKA option handling.
NegativeDefaultStepFunction() - Constructor for class weka.dl4j.stepfunctions.NegativeDefaultStepFunction
NegativeGradientStepFunction - Class in weka.dl4j.stepfunctions: A version of DeepLearning4j's NegativeGradientStepFunction that implements WEKA option handling.
NegativeGradientStepFunction() - Constructor for class weka.dl4j.stepfunctions.NegativeGradientStepFunction
Nesterovs - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's Nesterovs.
Nesterovs() - Constructor for class weka.dl4j.updater.Nesterovs
NeuralNetConfiguration - Class in weka.dl4j: A version of DeepLearning4j's NeuralNetConfiguration that implements WEKA option handling.
NeuralNetConfiguration() - Constructor for class weka.dl4j.NeuralNetConfiguration: Constructor that provides default values for the settings.
next() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Perform another epoch.
next() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Returns the next mini batch of data.
next(int) - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Returns a batch of the given size
next(int) - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
next() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
next(int) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
next(int) - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
next() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
nextSentence() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
nextSentence() - Method in class weka.dl4j.text.sentenceiterator.WekaInstanceSentenceIterator
nextToken() - Method in class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer
nextToken() - Method in class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer
NGramTokenizerFactory - Class in weka.dl4j.text.tokenization.tokenizer.factory: A DeepLearning4j's TokenizerFactory interface for Weka core tokenizers.
NGramTokenizerFactory() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
NGramTokenizerFactoryImpl - Class in weka.dl4j.text.tokenization.tokenizer.factory.impl: A DeepLearning4j's TokenizerFactory interface for Weka core tokenizers.
NGramTokenizerFactoryImpl() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
NoOp - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's ConstantScheduleImpl.
NoOp() - Constructor for class weka.dl4j.updater.NoOp
NoParamLayer<T extends org.deeplearning4j.nn.conf.layers.NoParamLayer> - Class in weka.dl4j.layers: Wrapper for DL4J NoParamLayer.
NoParamLayer() - Constructor for class weka.dl4j.layers.NoParamLayer
NormalDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's NormalDistribution that implements WEKA option handling.
NormalDistribution() - Constructor for class weka.dl4j.distribution.NormalDistribution
notDefaultFileLocation(File) - Static method in class weka.dl4j.Utils: Checks if the given file isn't the default file location (i.e., the user has selected a file).
numExamples() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
numExamples() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
numLabelClasses() - Method in class weka.dl4j.iterators.provider.CollectionLabeledSentenceProvider
numLabelClasses() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider

O

onEpochEnd(Model) - Method in class weka.dl4j.listener.EpochListener
open(Dl4jCNNExplorer) - Method in class weka.gui.explorer.SaliencyMapWindow: Show the saliency map.
OrthogonalDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's OrthogonalDistribution that implements WEKA option handling.
OrthogonalDistribution() - Constructor for class weka.dl4j.distribution.OrthogonalDistribution
OutputLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's OutputLayer that implements WEKA option handling.
OutputLayer() - Constructor for class weka.dl4j.layers.OutputLayer: Constructor for setting some defaults.
outputSingle(INDArray) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Convenience method to allow the Dl4j Inference panel to call outputSingle for a single image

P

parseClassmap(Instances) - Static method in class weka.dl4j.inference.ModelOutputDecoder: Get a classmap from a set of instances.
parseClassmapFromArff(String) - Static method in class weka.dl4j.inference.ModelOutputDecoder: Parse a classmap from a valid .arff file.
parseClassmapFromCsv(String) - Static method in class weka.dl4j.inference.ModelOutputDecoder: Parse a classmap from a valid .csv dataset.
pathExists(String) - Static method in class weka.dl4j.Utils: Checks whether the path exists - a little tidier than the code it wraps.
PMML_FILE_EXTENSION - Static variable in class weka.gui.explorer.ExplorerDl4jInference: The filename extension that should be used for PMML xml files.
PolySchedule - Class in weka.dl4j.schedules: Polynomial decay schedule for learning rates.
PolySchedule() - Constructor for class weka.dl4j.schedules.PolySchedule
PoolingType - Enum in weka.dl4j.enums: Proxy Enum for PoolingType.
poolNDArray(INDArray, PoolingType) - Static method in class weka.dl4j.Utils: Applies the pooling function to the given feature map.
postExecution() - Method in class weka.core.converters.ImageDirectoryLoader
postExecution() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.dl4j.IsGPUAvailable: Perform any teardown stuff that might need to happen after execution.
Prediction - Class in weka.dl4j.inference: Simple immutable class to hold the necessary values for prediction.
Prediction(PredictionClass, double) - Constructor for class weka.dl4j.inference.Prediction: Create a new prediction from the given class and probability.
Prediction(int, String, double) - Constructor for class weka.dl4j.inference.Prediction: Create a new prediction class.
PredictionClass - Class in weka.dl4j.inference: Wrapper class to hold a class ID and classname.
PredictionClass(int, String) - Constructor for class weka.dl4j.inference.PredictionClass: Create a new PredictionClass.
preExecution() - Method in class weka.core.converters.ImageDirectoryLoader
preExecution() - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Perform any setup stuff that might need to happen before execution.
preExecution() - Method in class weka.dl4j.IsGPUAvailable: Perform any setup stuff that might need to happen before execution.
Preferences - Class in weka.dl4j: Preferences class for Deeplearning4j/Nd4j static settings that should be used across the package.
Preferences() - Constructor for class weka.dl4j.Preferences
preProcess(String) - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl
pretrainedChecksum(PretrainedType) - Method in class weka.dl4j.zoo.keras.KerasZooModel
PretrainedType - Enum in weka.dl4j.enums: Proxy Enum for PretrainedType.
pretrainedUrl(PretrainedType) - Method in class weka.dl4j.zoo.keras.KerasZooModel
process(INDArray, String[]) - Method in class weka.dl4j.inference.TopNPredictions: Main entrypoint, decodes predictions into a TopNPredictions object.
processImage(File) - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Performs prediction and (optionally) computes a saliency map.
processImage(File) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator: Main processing entrypoint.
processImage(File) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Main processing entrypoint.
processImage(File) - Method in class weka.dl4j.interpretability.ScoreCAM
processImage(File) - Method in class weka.dl4j.interpretability.WekaScoreCAM
ProgressManager - Class in weka.core.progress: Main entrypoint for any progress-bar related tasks.
ProgressManager(double, String) - Constructor for class weka.core.progress.ProgressManager: Init a new progress manager, setting the maximum progress and progress message.
ProgressManager(String) - Constructor for class weka.core.progress.ProgressManager: Init a new indeterminate progress manager (no notion of iterating progress).
ProgressManager() - Constructor for class weka.core.progress.ProgressManager: Init the progress manager.

R

refreshDisplay() - Method in class weka.core.progress.AbstractProgressBar: Update the progress bar display.
refreshDisplay() - Method in class weka.core.progress.CommandLineProgressBar: Update the progress bar display.
refreshDisplay() - Method in class weka.core.progress.GUIProgressBar: Update the progress bar display.
RelationalDataSetIterator - Class in weka.dl4j.iterators.dataset.sequence: A DataSetIterator implementation that parses Instances with relational attributes.
RelationalDataSetIterator(Instances, int, int, int) - Constructor for class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator: Constructor.
RelationalInstanceIterator - Class in weka.dl4j.iterators.instance.sequence: Converts the given Instances containing a single relational attribute into a DataSet.
RelationalInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
remove() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Enables removing of a mini-batch.
remove() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
removeFromParent() - Method in class weka.gui.explorer.ClassSelector: Remove ourselves from the parent panel.
requiresPreProcessing() - Method in class weka.dl4j.zoo.AbstractZooModel: Does the model require input images to be preprocessed?.
reset() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Resets the cursor.
reset() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
reset() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
reset() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
reset() - Method in class weka.dl4j.text.sentenceiterator.WekaInstanceSentenceIterator
resetModelFilepath() - Method in class weka.dl4j.inference.CustomModelSetup: Reset the model filepath to the default.
resetSupported() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Whether the iterator can be reset.
resetSupported() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
resetSupported() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
reshapeActivations(INDArray, PoolingType) - Static method in class weka.dl4j.Utils: Reshape the activations, either by pooling or simply multiplying the extra dimensions together.
ResizeImageInstanceIterator - Class in weka.dl4j.iterators.instance: An iterator that loads images and resizes them.
ResizeImageInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.ResizeImageInstanceIterator: Empty constructor for Weka
ResizeImageInstanceIterator(ImageInstanceIterator, int, int) - Constructor for class weka.dl4j.iterators.instance.ResizeImageInstanceIterator: Default constructor with the new shape
ResNet - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of ResNet.
ResNet() - Constructor for class weka.dl4j.zoo.keras.ResNet: Instantiate the model.
ResNet.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
ResourceResolver - Class in weka.dl4j
ResourceResolver() - Constructor for class weka.dl4j.ResourceResolver
RmsProp - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's RmsProp.
RmsProp() - Constructor for class weka.dl4j.updater.RmsProp
RnnOutputLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's RnnOutputLayer that implements WEKA option handling.
RnnOutputLayer() - Constructor for class weka.dl4j.layers.RnnOutputLayer: Constructor for setting some defaults.
RnnSequenceClassifier - Class in weka.classifiers.functions: A classifier that can handle sequences.
RnnSequenceClassifier() - Constructor for class weka.classifiers.functions.RnnSequenceClassifier
RnnTextEmbeddingDataSetIterator - Class in weka.dl4j.iterators.dataset.sequence.text.rnn: A DataSetIterator implementation that reads text documents from an arff file and translates each document to a sequence of wordvectors, given a wordvector model.
RnnTextEmbeddingDataSetIterator(Instances, WordVectors, TokenizerFactory, TokenPreProcess, AbstractStopwords, LabeledSentenceProvider, int, int) - Constructor for class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator: Constructor with necessary objects to create RNN features.
RnnTextEmbeddingInstanceIterator - Class in weka.dl4j.iterators.instance.sequence.text.rnn: Converts the given Instances object into a DataSet and then constructs and returns a RnnTextEmbeddingInstanceIterator.
RnnTextEmbeddingInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator
RnnTextFilesEmbeddingInstanceIterator - Class in weka.dl4j.iterators.instance.sequence.text.rnn: Converts the given Instances object into a DataSet and then constructs and returns a RnnTextEmbeddingInstanceIterator.
RnnTextFilesEmbeddingInstanceIterator() - Constructor for class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
run(Object, String[]) - Method in class weka.core.converters.ImageDirectoryLoader
run() - Method in class weka.core.progress.GUIProgressBar
run(Object, String[]) - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Execute the supplied object.
run(Object, String[]) - Method in class weka.dl4j.IsGPUAvailable: Execute the supplied object.
runWithLocalClassloader(Class, VoidCallable) - Static method in class weka.dl4j.Utils: Run some code-block using the local class loader from a given class.

S

SaliencyMapGBC() - Constructor for class weka.gui.explorer.SaliencyMapWindow.SaliencyMapGBC: Init.
SaliencyMapGBC(int) - Constructor for class weka.gui.explorer.SaliencyMapWindow.SaliencyMapGBC: Init.
SaliencyMapWindow - Class in weka.gui.explorer: JPanel showing the saliency map generated, as well as options for configuring it.
SaliencyMapWindow() - Constructor for class weka.gui.explorer.SaliencyMapWindow: Initialize the window.
SaliencyMapWindow.SaliencyMapGBC - Class in weka.gui.explorer: Wrapper class for GBC which defaults to inset size of 5.
SameDiffLayer<T extends org.deeplearning4j.nn.conf.layers.samediff.SameDiffLambdaLayer> - Class in weka.dl4j.layers: Abstract SameDiff layer.
SameDiffLayer() - Constructor for class weka.dl4j.layers.SameDiffLayer
saveResult(BufferedImage) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Save the supplied composite image to a file.
Schedule<T extends org.nd4j.linalg.schedule.ISchedule> - Class in weka.dl4j.schedules: Default schedule interface that implements WEKA option handling.
Schedule() - Constructor for class weka.dl4j.schedules.Schedule
ScheduleType - Enum in weka.dl4j.schedules: Proxy Enum for ScheduleType.
ScoreCAM - Class in weka.dl4j.interpretability: Implementation of the ScoreCAM saliency map generation method.
ScoreCAM() - Constructor for class weka.dl4j.interpretability.ScoreCAM
SeperableConvolution2DLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's SeperableConvolution2DLayer that implements WEKA option handling.
SeperableConvolution2DLayer() - Constructor for class weka.dl4j.layers.SeperableConvolution2DLayer: Constructor for setting some defaults.
setAction(Dl4jStringToWordEmbeddings.Action) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setActivationFunction(Activation) - Method in class weka.dl4j.layers.ActivationLayer
setActivationFunction(Activation) - Method in class weka.dl4j.layers.FeedForwardLayer
setAdditive(boolean) - Method in class weka.dl4j.weightnoise.WeightNoise
setAllowParallelTokenization(boolean) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setAlpha(double) - Method in class weka.dl4j.activations.ActivationELU
setAlpha(double) - Method in class weka.dl4j.activations.ActivationLReLU
setAlpha(double) - Method in class weka.dl4j.dropout.AlphaDropout
setAlpha(double) - Method in class weka.dl4j.layers.CenterLossOutputLayer
setAppend(boolean) - Method in class weka.core.LogConfiguration: Whether to append to the existing log file or not.
setApplyToBias(boolean) - Method in class weka.dl4j.weightnoise.WeightNoise
setBackend(T) - Method in class weka.dl4j.activations.Activation
setBackend(ActivationELU) - Method in class weka.dl4j.activations.ActivationELU
setBackend(ActivationRReLU) - Method in class weka.dl4j.activations.ActivationRReLU
setBackend(T) - Method in interface weka.dl4j.ApiWrapper: Set the DL4J backend.
setBackend(T) - Method in class weka.dl4j.distribution.Distribution
setBackend(T) - Method in class weka.dl4j.dropout.AbstractDropout
setBackend(ConvolutionLayer.AlgoMode) - Method in enum weka.dl4j.enums.AlgoMode
setBackend(ConvolutionMode) - Method in enum weka.dl4j.enums.ConvolutionMode
setBackend(GradientNormalization) - Method in enum weka.dl4j.enums.GradientNormalization
setBackend(PoolingType) - Method in enum weka.dl4j.enums.PoolingType
setBackend(PretrainedType) - Method in enum weka.dl4j.enums.PretrainedType
setBackend(CustomBroadcast) - Method in class weka.dl4j.layers.BroadcastLambdaLayer
setBackend(T) - Method in class weka.dl4j.layers.Layer
setBackend(T) - Method in class weka.dl4j.lossfunctions.LossFunction
setBackend(ConstantSchedule.ConstantScheduleImpl) - Method in class weka.dl4j.schedules.ConstantSchedule
setBackend(ExponentialSchedule) - Method in class weka.dl4j.schedules.ExponentialSchedule
setBackend(InverseSchedule) - Method in class weka.dl4j.schedules.InverseSchedule
setBackend(MapSchedule) - Method in class weka.dl4j.schedules.MapSchedule
setBackend(PolySchedule) - Method in class weka.dl4j.schedules.PolySchedule
setBackend(ScheduleType) - Method in enum weka.dl4j.schedules.ScheduleType
setBackend(SigmoidSchedule) - Method in class weka.dl4j.schedules.SigmoidSchedule
setBackend(StepSchedule) - Method in class weka.dl4j.schedules.StepSchedule
setBackend(T) - Method in class weka.dl4j.stepfunctions.StepFunction
setBackend(T) - Method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess
setBackend(T) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory
setBackend(T) - Method in class weka.dl4j.updater.Updater
setBackend(T) - Method in class weka.dl4j.weightnoise.AbstractWeightNoise
setBatchSize(int) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setBatchSize(int) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setBatchSize(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setBeta(double) - Method in class weka.dl4j.layers.BatchNormalization
setBeta1(double) - Method in class weka.dl4j.updater.Adam
setBeta1(double) - Method in class weka.dl4j.updater.AdaMax
setBeta1(double) - Method in class weka.dl4j.updater.Nadam
setBeta2(double) - Method in class weka.dl4j.updater.Adam
setBeta2(double) - Method in class weka.dl4j.updater.AdaMax
setBeta2(double) - Method in class weka.dl4j.updater.Nadam
setBiasInit(double) - Method in class weka.dl4j.NeuralNetConfiguration
setBiasUpdater(Updater) - Method in class weka.dl4j.NeuralNetConfiguration
setBuiltInClassMap(ClassmapType) - Method in class weka.dl4j.inference.ModelOutputDecoder
setCacheMode(CacheMode) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setChannelsLast(boolean) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
setChannelsLast(boolean) - Method in class weka.dl4j.zoo.AbstractZooModel
setClassMap(String[]) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setClassMapFile(File) - Method in class weka.dl4j.inference.ModelOutputDecoder
setCollapseDimensions(boolean) - Method in class weka.dl4j.layers.GlobalPoolingLayer
setComputationGraph(ComputationGraph) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setConcat_words(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setConcatWords(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setConvolutionMode(ConvolutionMode) - Method in class weka.dl4j.layers.ConvolutionLayer
setConvolutionMode(ConvolutionMode) - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer
setConvolutionMode(ConvolutionMode) - Method in class weka.dl4j.layers.SubsamplingLayer
setCudnnAlgoMode(AlgoMode) - Method in class weka.dl4j.layers.ConvolutionLayer
setCudnnAlgoMode(AlgoMode) - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer
setCursor(int) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
setCustomModelSetup(CustomModelSetup) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setCustomModelSetup(CustomModelSetup) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setDecay(double) - Method in class weka.dl4j.layers.BatchNormalization
setDecayRate(double) - Method in class weka.dl4j.schedules.StepSchedule
setDelimiters(String) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
setDelimiters(String) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
setDist(Distribution<? extends Distribution>) - Method in class weka.dl4j.NeuralNetConfiguration
setDistribution(Distribution<? extends Distribution>) - Method in class weka.dl4j.weightnoise.WeightNoise
setDl4jLogLevel(LogConfiguration.LogLevel) - Method in class weka.core.LogConfiguration: Set the Dl4j log level.
setDl4jMlpClassifier(Dl4jMlpClassifier) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setDoNotClearFilesystemCache(boolean) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setDropout(AbstractDropout) - Method in class weka.dl4j.layers.DropoutLayer
setDropout(AbstractDropout) - Method in class weka.dl4j.NeuralNetConfiguration
setEarlyStopping(EarlyStopping) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setEmbedding_prefix(String) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setEnableScavenger(boolean) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setEpochs(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setEps(double) - Method in class weka.dl4j.layers.BatchNormalization
setEps(double) - Method in class weka.dl4j.layers.SubsamplingLayer
setEpsilon(double) - Method in class weka.dl4j.updater.AdaDelta
setEpsilon(double) - Method in class weka.dl4j.updater.AdaGrad
setEpsilon(double) - Method in class weka.dl4j.updater.Adam
setEpsilon(double) - Method in class weka.dl4j.updater.AdaMax
setEpsilon(double) - Method in class weka.dl4j.updater.Nadam
setEpsilon(double) - Method in class weka.dl4j.updater.RmsProp
setExplorer(Explorer) - Method in class weka.gui.explorer.ExplorerDl4jInference: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExtraLayersToRemove(String[]) - Method in class weka.dl4j.zoo.AbstractZooModel
setFeatureExtractionLayer(String) - Method in class weka.dl4j.zoo.AbstractZooModel
setFieldValue(Object, String, T) - Static method in class weka.dl4j.Utils: Set private field of a given object.
setFilterMode(boolean) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setGain(double) - Method in class weka.dl4j.distribution.OrthogonalDistribution
setGamma(double) - Method in class weka.dl4j.layers.BatchNormalization
setGamma(double) - Method in class weka.dl4j.schedules.ExponentialSchedule
setGamma(double) - Method in class weka.dl4j.schedules.InverseSchedule
setGamma(double) - Method in class weka.dl4j.schedules.SigmoidSchedule
setGateActivationFn(Activation) - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.
setGateActivationFn(Activation) - Method in class weka.dl4j.layers.LSTM
setGenerateSaliencyMap(boolean) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setGradientCheck(boolean) - Method in class weka.dl4j.layers.CenterLossOutputLayer
setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.NeuralNetConfiguration
setGradientNormalizationThreshold(double) - Method in class weka.dl4j.NeuralNetConfiguration
setHeight(int) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
setHeight(int) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
setHeight(int) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setImageChannelsLast(boolean) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setImageInstanceIterator(ImageInstanceIterator) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setImagePreProcessingScaler(ImagePreProcessingScaler) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setImagesLocation(File) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
setImagesLocation(File) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setIndeterminate(boolean) - Method in class weka.core.progress.AbstractProgressBar: Sets the indeterminate status of the progress bar
setInitialValue(double) - Method in class weka.dl4j.schedules.ConstantSchedule
setInitialValue(double) - Method in class weka.dl4j.schedules.MapSchedule: Deprecated.
setInitialValue(double) - Method in class weka.dl4j.schedules.Schedule
setInputChannels(int) - Method in class weka.dl4j.inference.CustomModelSetup
setInputDirectory(File) - Method in class weka.core.converters.ImageDirectoryLoader
setInputFilename(String) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setInputHeight(int) - Method in class weka.dl4j.inference.CustomModelSetup
setInputShape(int[][]) - Method in class weka.dl4j.zoo.keras.KerasZooModel
setInputWidth(int) - Method in class weka.dl4j.inference.CustomModelSetup
setInstanceIterator(AbstractInstanceIterator) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setInstanceIterator(AbstractInstanceIterator) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setInstances(Instances) - Method in class weka.gui.explorer.ExplorerDl4jInference: Tells the panel to use a new set of instances.
setIntermediateEvaluationsEnabled(boolean) - Method in class weka.dl4j.listener.EpochListener
setIterationListener(TrainingListener) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setIterations(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setKernelSize(int[]) - Method in class weka.dl4j.layers.ConvolutionLayer
setKernelSize(int[]) - Method in class weka.dl4j.layers.SubsamplingLayer
setKernelSizeX(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setKernelSizeX(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setKernelSizeY(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setKernelSizeY(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setL1(double) - Method in class weka.dl4j.NeuralNetConfiguration
setL2(double) - Method in class weka.dl4j.NeuralNetConfiguration
setLambda(double) - Method in class weka.dl4j.dropout.AlphaDropout
setLambda(double) - Method in class weka.dl4j.layers.CenterLossOutputLayer
setLayerName(String) - Method in class weka.dl4j.layers.Layer
setLayers(Layer...) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setLayerSize(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setLearningRate(double) - Method in class weka.dl4j.updater.AdaDelta: Set the learning rate
setLearningRate(double) - Method in class weka.dl4j.updater.Updater: Set the learning rate
setLearningRate(double) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setLearningRateSchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.updater.Updater: Set the learning rate schedule
setLoadLayerSpecification(boolean) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setLockGammaAndBeta(boolean) - Method in class weka.dl4j.layers.BatchNormalization
setLockGammaBeta(boolean) - Method in class weka.dl4j.layers.BatchNormalization
setLog(Logger) - Method in class weka.gui.explorer.ExplorerDl4jInference: Sets the Logger to receive informational messages
setLogConfig(LogConfiguration) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Set the log configuration.
setLogFile(File) - Method in class weka.core.LogConfiguration: Set the log file
setLossFn(LossFunction<? extends ILossFunction>) - Method in class weka.dl4j.layers.CenterLossOutputLayer
setLossFn(LossFunction<? extends ILossFunction>) - Method in class weka.dl4j.layers.LossLayer
setLossFn(LossFunction<? extends ILossFunction>) - Method in class weka.dl4j.layers.OutputLayer
setLossFn(LossFunction<? extends ILossFunction>) - Method in class weka.dl4j.layers.RnnOutputLayer
setLower(double) - Method in class weka.dl4j.distribution.UniformDistribution
setLowerBound(double) - Method in class weka.dl4j.activations.ActivationRReLU
setMaxEpochsNoImprovement(int) - Method in class weka.dl4j.earlystopping.EarlyStopping
setMaxIter(int) - Method in class weka.dl4j.schedules.PolySchedule
setMaxProgress(double) - Method in class weka.core.progress.AbstractProgressBar: Set the max progress value
setMaxProgress(double) - Method in class weka.core.progress.ProgressManager: Set the maximum progress value of the progress bar
setMean(double) - Method in class weka.dl4j.distribution.LogNormalDistribution
setMean(double) - Method in class weka.dl4j.distribution.NormalDistribution
setMean(double) - Method in class weka.dl4j.distribution.TruncatedNormalDistribution
setMinibatch(boolean) - Method in class weka.dl4j.layers.BatchNormalization
setMiniBatch(boolean) - Method in class weka.dl4j.NeuralNetConfiguration
setMinimize(boolean) - Method in class weka.dl4j.NeuralNetConfiguration
setMinLearningRate(double) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setMinWordFrequency(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setModelInputShape(InputType.InputTypeConvolutional) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setModelInputShape(InputType.InputTypeConvolutional) - Method in class weka.dl4j.interpretability.ScoreCAM
setModelName(String) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapGenerator
setModelOutputDecoder(ModelOutputDecoder) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setMomentum(double) - Method in class weka.dl4j.updater.Nesterovs
setN(int) - Method in class weka.dl4j.inference.TopNPredictions
setN(int) - Method in class weka.dl4j.listener.EpochListener
setNd4jLogLevel(LogConfiguration.LogLevel) - Method in class weka.core.LogConfiguration: Set the Nd4j log level.
setNegative(double) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setNeuralNetConfiguration(NeuralNetConfiguration) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setNMax(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
setNMax(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
setNMax(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
setNMax(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
setNMin(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory
setNMin(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
setNMin(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
setNMin(int) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory
setNormalizeHeatmap(boolean) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setNOut(long) - Method in class weka.dl4j.layers.BatchNormalization: Deprecated.
setNOut(long) - Method in class weka.dl4j.layers.ConvolutionLayer
setNOut(long) - Method in class weka.dl4j.layers.FeedForwardLayer
setNumberOfTrials(int) - Method in class weka.dl4j.distribution.BinomialDistribution
setNumChannels(int) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
setNumChannels(int) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
setNumChannels(int) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setNumEpochs(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setNumFExtractOutputs(int) - Method in class weka.dl4j.zoo.AbstractZooModel
setNumGPUs(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setOptimizationAlgo(OptimizationAlgorithm) - Method in class weka.dl4j.NeuralNetConfiguration
setOptions(String[]) - Method in class weka.core.converters.ImageDirectoryLoader: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.LogConfiguration: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.Activation: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationCube: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationELU: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationHardSigmoid: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationHardTanH: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationIdentity: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationLReLU: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationRationalTanh: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationReLU: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationRReLU: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationSigmoid: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationSoftmax: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationSoftPlus: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationSoftSign: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationSwish: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.activations.ActivationTanH: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.BinomialDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.ConstantDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.Distribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.LogNormalDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.NormalDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.OrthogonalDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.TruncatedNormalDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.distribution.UniformDistribution: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.dropout.AbstractDropout: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.dropout.AlphaDropout: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.dropout.Dropout: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.dropout.GaussianDropout: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.dropout.GaussianNoise: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.earlystopping.EarlyStopping: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.inference.CustomModelSetup: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.inference.Dl4jCNNExplorer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.inference.ModelOutputDecoder: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.IsGPUAvailable: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.ActivationLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.BatchNormalization: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.BroadcastLambdaLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.CenterLossOutputLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.ConvolutionLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.Cropping2D: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.DenseLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.DepthwiseConvolution2DLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.DropoutLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.FeedForwardLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.GlobalPoolingLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.GravesLSTM: Deprecated.

Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.Layer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.LocalResponseNormalization: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.LossLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.LSTM: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.NoParamLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.OutputLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.RnnOutputLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.SameDiffLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.SeperableConvolution2DLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.SubsamplingLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.layers.ZeroPaddingLayer: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.listener.TrainingListener: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossBinaryXENT: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossCosineProximity: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossFMeasure: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossHinge: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossKLD: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossL1: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossL2: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMAE: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMAPE: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMCXENT: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMixtureDensity: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMSE: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMSLE: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossMultiLabel: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossNegativeLogLikelihood: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossPoisson: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.lossfunctions.LossSquaredHinge: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.NeuralNetConfiguration: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.ConstantSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.ExponentialSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.InverseSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.MapSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.PolySchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.Schedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.SigmoidSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.schedules.StepSchedule: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.stepfunctions.DefaultStepFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.stepfunctions.GradientStepFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.stepfunctions.NegativeDefaultStepFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.stepfunctions.NegativeGradientStepFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.stepfunctions.StepFunction: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.CommonPreProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.EndingPreProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.LowCasePreProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.CharacterNGramTokenizerFactory: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.DefaultTokenizerFactory: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.NGramTokenizerFactory: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.AdaDelta: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.AdaGrad: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.Adam: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.AdaMax: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.Nadam: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.Nesterovs: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.RmsProp: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.Sgd: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.updater.Updater: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.weightnoise.AbstractWeightNoise: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.weightnoise.DropConnect: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.weightnoise.WeightNoise: Parses a given list of options.
setOptions(String[]) - Method in class weka.dl4j.zoo.AbstractZooModel: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings: Parses the options for this object.
setOutputFile(File) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setOutputFileName(String) - Method in class weka.core.converters.ImageDirectoryLoader
setOutputLayer(String) - Method in class weka.dl4j.zoo.AbstractZooModel
setP(double) - Method in class weka.dl4j.dropout.AlphaDropout
setP(double) - Method in class weka.dl4j.dropout.Dropout
setPadding(int[]) - Method in class weka.dl4j.layers.ConvolutionLayer
setPadding(int[]) - Method in class weka.dl4j.layers.SubsamplingLayer
setPadding(int[]) - Method in class weka.dl4j.layers.ZeroPaddingLayer
setPaddingColumns(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setPaddingColumns(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setPaddingColumns(int) - Method in class weka.dl4j.layers.ZeroPaddingLayer
setPaddingRows(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setPaddingRows(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setPaddingRows(int) - Method in class weka.dl4j.layers.ZeroPaddingLayer
setParameterAveragingFrequency(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setPnorm(int) - Method in class weka.dl4j.layers.GlobalPoolingLayer
setPnorm(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setPoolingDimensions(int[]) - Method in class weka.dl4j.layers.GlobalPoolingLayer
setPoolingType(PoolingType) - Method in class weka.dl4j.layers.GlobalPoolingLayer
setPoolingType(PoolingType) - Method in class weka.dl4j.layers.SubsamplingLayer
setPoolingType(PoolingType) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setPower(double) - Method in class weka.dl4j.schedules.InverseSchedule
setPower(double) - Method in class weka.dl4j.schedules.PolySchedule
setPrefetchBufferSize(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setPreProcessor(DataSetPreProcessor) - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Sets the preprocessor.
setPreProcessor(DataSetPreProcessor) - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
setPreProcessor(DataSetPreProcessor) - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
setPreProcessor(TokenPreProcess) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings: Sets the preprocessor action.
setPretrainedType(PretrainedType) - Method in class weka.dl4j.zoo.AbstractZooModel
setPretrainedType(PretrainedType) - Method in class weka.dl4j.zoo.Dl4jVGG
setProbabilityOfSuccess(double) - Method in class weka.dl4j.distribution.BinomialDistribution
setProgress(double) - Method in class weka.core.progress.AbstractProgressBar: Main update method.
setProgress(double) - Method in class weka.core.progress.ProgressManager: Set the progress to a specific value
setProgressMessage(String) - Method in class weka.core.progress.AbstractProgressBar: Set the progress message
setProgressMessage(String) - Method in class weka.core.progress.ProgressManager: Set the progress message to be displayed in the progress bar
setpSchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.dropout.AlphaDropout
setpSchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.dropout.Dropout
setQueueSize(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier
setRateSchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.dropout.GaussianDropout
setRateSchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.dropout.GaussianNoise
setRelationalAttributeIndex(int) - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
setRequiresPooling(boolean) - Method in class weka.dl4j.zoo.AbstractZooModel
setResume(boolean) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setRho(double) - Method in class weka.dl4j.updater.AdaDelta
setRmsDecay(double) - Method in class weka.dl4j.updater.RmsProp
setSaliencyMapWrapper(AbstractCNNSaliencyMapWrapper) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setSampling(double) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setScheduleType(ScheduleType) - Method in class weka.dl4j.schedules.Schedule
setSeed(long) - Method in class weka.dl4j.NeuralNetConfiguration
setSeed(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setSerializedModelFile(File) - Method in class weka.dl4j.inference.CustomModelSetup
setSerializedModelFile(File) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setSource(File) - Method in class weka.core.converters.ImageDirectoryLoader
setSource(File) - Method in class weka.core.converters.Word2VecLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setStd(double) - Method in class weka.dl4j.distribution.LogNormalDistribution
setStd(double) - Method in class weka.dl4j.distribution.NormalDistribution
setStd(double) - Method in class weka.dl4j.distribution.TruncatedNormalDistribution
setStdDev(double) - Method in class weka.dl4j.dropout.GaussianNoise
setStemmer(Stemmer) - Method in class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl
setStemmer(Stemmer) - Method in class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor
setStep(double) - Method in class weka.dl4j.schedules.StepSchedule
setStepSize(int) - Method in class weka.dl4j.schedules.SigmoidSchedule
setStopwords(Dl4jAbstractStopwords) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
setStopWordsHandler(Dl4jAbstractStopwords) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setStride(int[]) - Method in class weka.dl4j.layers.ConvolutionLayer
setStride(int[]) - Method in class weka.dl4j.layers.SubsamplingLayer
setStrideColumns(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setStrideColumns(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setStrideRows(int) - Method in class weka.dl4j.layers.ConvolutionLayer
setStrideRows(int) - Method in class weka.dl4j.layers.SubsamplingLayer
setStructure() - Method in class weka.core.converters.Word2VecLoader
setTargetClass(int) - Method in class weka.gui.explorer.ClassSelector
setTargetClassIDs(String) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
setTargetClassIDsAsInt(int[]) - Method in class weka.dl4j.interpretability.AbstractCNNSaliencyMapWrapper
settBPTTbackwardLength(int) - Method in class weka.classifiers.functions.RnnSequenceClassifier
settBPTTforwardLength(int) - Method in class weka.classifiers.functions.RnnSequenceClassifier
setTextIndex(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings: Set the attribute's index with the string to process.
setTextsLocation(File) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
setTextsLocation(File) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator
setTokenizerFactory(TokenizerFactory) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
setTokenizerFactory(TokenizerFactory) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setTokenPreProcess(TokenPreProcess) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
setTokenPreProcessor(TokenPreProcess) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.CharacterNGramTokenizerFactoryImpl
setTokenPreProcessor(TokenPreProcess) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.NGramTokenizerFactoryImpl
setTokenPreProcessor(TokenPreProcess) - Method in class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl
setTokenPreProcessor(TokenPreProcess) - Method in class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer
setTokenPreProcessor(TokenPreProcess) - Method in class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer
setTrainBatchSize(int) - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Setting the training batch size
setTrainBatchSize(int) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setTransformationLayerNames(String[]) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setTransformationLayers(DenseLayer[]) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setTruncateLength(int) - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
setTruncateLength(int) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
setUnknown(INDArray) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
setUnknownWordHandling(CnnSentenceDataSetIterator.UnknownWordHandling) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
setUpdater(Updater) - Method in class weka.dl4j.NeuralNetConfiguration
setUpper(double) - Method in class weka.dl4j.distribution.UniformDistribution
setUpperBound(double) - Method in class weka.dl4j.activations.ActivationRReLU
setUseAdaGrad(boolean) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setUseCustomModel(boolean) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setUseCustomSetup(boolean) - Method in class weka.dl4j.inference.CustomModelSetup
setUseDefaultFeatureLayer(boolean) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter
setUseHierarchicSoftmax(boolean) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWord2Vec
setUseNormalizedWordVectors(boolean) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
setValidationSetPercentage(double) - Method in class weka.dl4j.earlystopping.EarlyStopping
setValue(double) - Method in class weka.dl4j.distribution.ConstantDistribution
setValues(Map<Integer, Double>) - Method in class weka.dl4j.schedules.MapSchedule
setVariation(Dl4jDarknet19.VARIATION) - Method in class weka.dl4j.zoo.Dl4jDarknet19
setVariation(VGG.VARIATION) - Method in class weka.dl4j.zoo.Dl4jVGG
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.DenseNet
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.EfficientNet
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.InceptionResNetV2
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.InceptionV3
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.KerasZooModel
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.MobileNet
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.NASNet
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.ResNet
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.VGG
setVariation(Enum) - Method in class weka.dl4j.zoo.keras.Xception
setVariation(DenseNet.VARIATION) - Method in class weka.dl4j.zoo.KerasDenseNet
setVariation(EfficientNet.VARIATION) - Method in class weka.dl4j.zoo.KerasEfficientNet
setVariation(InceptionV3.VARIATION) - Method in class weka.dl4j.zoo.KerasInceptionV3
setVariation(NASNet.VARIATION) - Method in class weka.dl4j.zoo.KerasNASNet
setVariation(ResNet.VARIATION) - Method in class weka.dl4j.zoo.KerasResNet
setVariation(VGG.VARIATION) - Method in class weka.dl4j.zoo.KerasVGG
setVariation(Xception.VARIATION) - Method in class weka.dl4j.zoo.KerasXception
setWeightInit(WeightInit) - Method in class weka.dl4j.NeuralNetConfiguration
setWeightNoise(AbstractWeightNoise) - Method in class weka.dl4j.NeuralNetConfiguration
setWeightRetainProbability(double) - Method in class weka.dl4j.weightnoise.DropConnect
setWeightRetainProbabilitySchedule(Schedule<? extends ISchedule>) - Method in class weka.dl4j.weightnoise.DropConnect
setWekaDl4jLogLevel(LogConfiguration.LogLevel) - Method in class weka.core.LogConfiguration: Set the WekaDeeplearning4j log level.
setWidth(int) - Method in class weka.dl4j.iterators.instance.ConvolutionInstanceIterator
setWidth(int) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator
setWidth(int) - Method in class weka.dl4j.iterators.instance.ResizeImageInstanceIterator
setWindowSize(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setWordVectorLocation(File) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator: Set the word vector location and try to initialize it
setWordVectors(WordVectors) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator
setWordVectors(WordVectors) - Method in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator
setWorkers(int) - Method in class weka.filters.unsupervised.attribute.Dl4jStringToWordEmbeddings
setZooModel(AbstractZooModel) - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Set the modelzoo zooModel
setZooModel(AbstractZooModel) - Method in class weka.classifiers.functions.RnnSequenceClassifier: Deprecated.
setZooModelType(AbstractZooModel) - Method in class weka.dl4j.inference.Dl4jCNNExplorer
setZooModelType(AbstractZooModel) - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Clear the old transformation layers and set the new one if we've changed to a different model type.
Sgd - Class in weka.dl4j.updater: A WEKA version of DeepLearning4j's Sgd.
Sgd() - Constructor for class weka.dl4j.updater.Sgd
SigmoidSchedule - Class in weka.dl4j.schedules: Sigmoid schedule for learning rates.
SigmoidSchedule() - Constructor for class weka.dl4j.schedules.SigmoidSchedule
splitTrainVal(Instances, double) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: Split the dataset into p% train an (100-p)% test set.
start() - Method in class weka.core.progress.AbstractProgressBar: Initialize all values to 0 and start the progress manager.
start() - Method in class weka.core.progress.ProgressManager: Show the progress bar and start the timer.
StemmingPreProcessor - Class in weka.dl4j.text.tokenization.preprocessor: A wrapper that extends the PreProcessor API for StemmingPreProcessorImpl.
StemmingPreProcessor() - Constructor for class weka.dl4j.text.tokenization.preprocessor.StemmingPreProcessor
StemmingPreProcessorImpl - Class in weka.dl4j.text.tokenization.preprocessor.impl: Implements basic cleaning inherited from CommonPreProcessor + does stemming using a Weka Stemmer.
StemmingPreProcessorImpl() - Constructor for class weka.dl4j.text.tokenization.preprocessor.impl.StemmingPreProcessorImpl
StepFunction<T extends org.deeplearning4j.nn.conf.stepfunctions.StepFunction> - Class in weka.dl4j.stepfunctions: StepFunction wrapper for Deeplearning4j's StepFunction classes.
StepFunction() - Constructor for class weka.dl4j.stepfunctions.StepFunction
StepSchedule - Class in weka.dl4j.schedules: Step schedule for learning rates.
StepSchedule() - Constructor for class weka.dl4j.schedules.StepSchedule
stopwords(AbstractStopwords) - Method in class weka.dl4j.iterators.dataset.sequence.text.cnn.CnnSentenceDataSetIterator.Builder: Set stopwords.
stopwordsTipText() - Method in class weka.dl4j.text.stopwords.Dl4jWordsFromFile: Returns the tip text for this property.
SubsamplingLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's SubsamplingLayer that implements WEKA option handling.
SubsamplingLayer() - Constructor for class weka.dl4j.layers.SubsamplingLayer: Constructor for setting some defaults.

T

TAGS_FILTER - Static variable in class weka.classifiers.functions.Dl4jMlpClassifier: The filter to apply to the training data.
textProgressBarTest() - Static method in class weka.examples.WekaDeeplearning4jExamples
TokenizerFactory<T extends org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory> - Class in weka.dl4j.text.tokenization.tokenizer.factory: TokenizerFactory wrapper for Deeplearning4j's TokenizerFactory classes.
TokenizerFactory() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.TokenizerFactory
TokenPreProcess<T extends org.deeplearning4j.text.tokenization.tokenizer.TokenPreProcess> - Class in weka.dl4j.text.tokenization.preprocessor: TokenPreProcess wrapper for Deeplearning4j's TokenPreProcess classes.
TokenPreProcess() - Constructor for class weka.dl4j.text.tokenization.preprocessor.TokenPreProcess
TopNPredictions - Class in weka.dl4j.inference: Holds an arbitrary number of predictions, ordered by class probability.
TopNPredictions() - Constructor for class weka.dl4j.inference.TopNPredictions: Initialize.
TopNPredictions(String, String) - Constructor for class weka.dl4j.inference.TopNPredictions: Initialize the top N predictions.
toString() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Returns a string describing the model.
toString() - Method in class weka.dl4j.inference.Prediction
toString() - Method in class weka.dl4j.inference.PredictionClass
toSummaryString() - Method in class weka.dl4j.inference.TopNPredictions: Return a summary string of the stored predictions.
toSummaryString(String, String) - Method in class weka.dl4j.inference.TopNPredictions: Return a summary string of the stored predictions, headed with the given image and model name.
toTableRowString(String) - Method in class weka.dl4j.inference.Prediction: Output a nicely formatted string for this prediction.
totalNumSentences() - Method in class weka.dl4j.iterators.provider.FileLabeledSentenceProvider
totalOutcomes() - Method in class weka.dl4j.iterators.dataset.DefaultDataSetIterator: Returns the total number of labels.
totalOutcomes() - Method in class weka.dl4j.iterators.dataset.sequence.RelationalDataSetIterator
totalOutcomes() - Method in class weka.dl4j.iterators.dataset.sequence.text.rnn.RnnTextEmbeddingDataSetIterator
TrainingListener - Class in weka.dl4j.listener: Iteration listener that can be attached to a Dl4j model.
TrainingListener() - Constructor for class weka.dl4j.listener.TrainingListener
transformationLayersToNames() - Method in class weka.filters.unsupervised.attribute.Dl4jMlpFilter: Return transformation layer names.
TruncatedNormalDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's TruncatedNormalDistribution that implements WEKA option handling.
TruncatedNormalDistribution() - Constructor for class weka.dl4j.distribution.TruncatedNormalDistribution
tryLoadFromFile(File, AbstractZooModel) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier: Tries to load from a saved model file (if it exists), otherwise loads the given zoo model
TweetNLPTokenizer - Class in weka.dl4j.text.tokenization.tokenizer: A DeepLearning4j's Tokenizer interface for the CMU TweetNLP tokenizer.
TweetNLPTokenizer(String) - Constructor for class weka.dl4j.text.tokenization.tokenizer.TweetNLPTokenizer: initializes the Object
TweetNLPTokenizerFactory - Class in weka.dl4j.text.tokenization.tokenizer.factory: A DeepLearning4j's TokenizerFactory interface for the CMU TweetNLP tokenizer.
TweetNLPTokenizerFactory() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.TweetNLPTokenizerFactory
TweetNLPTokenizerFactoryImpl - Class in weka.dl4j.text.tokenization.tokenizer.factory.impl: A DeepLearning4j's TokenizerFactory interface for the CMU TweetNLP tokenizer.
TweetNLPTokenizerFactoryImpl() - Constructor for class weka.dl4j.text.tokenization.tokenizer.factory.impl.TweetNLPTokenizerFactoryImpl

U

UniformDistribution - Class in weka.dl4j.distribution: A version of DeepLearning4j's UniformDistribution that implements WEKA option handling.
UniformDistribution() - Constructor for class weka.dl4j.distribution.UniformDistribution
Updater<T extends org.nd4j.linalg.learning.config.IUpdater> - Class in weka.dl4j.updater: Default Updater that implements WEKA option handling.
Updater() - Constructor for class weka.dl4j.updater.Updater
useEarlyStopping() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Use early stopping only if valid split percentage
useZooModel() - Method in class weka.classifiers.functions.Dl4jMlpClassifier: Check if the user has selected to use a zoomodel
Utils - Class in weka.dl4j: Utility routines for the Dl4jMlpClassifier.
Utils() - Constructor for class weka.dl4j.Utils

V

validate(Instances) - Method in class weka.dl4j.iterators.instance.AbstractInstanceIterator: Validates the input dataset
validate(Instances) - Method in class weka.dl4j.iterators.instance.DefaultInstanceIterator
validate(Instances) - Method in class weka.dl4j.iterators.instance.ImageInstanceIterator: Validates the input dataset.
validate(Instances) - Method in class weka.dl4j.iterators.instance.sequence.RelationalInstanceIterator
validate(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextEmbeddingInstanceIterator
validate(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.cnn.CnnTextFilesEmbeddingInstanceIterator
validate(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextEmbeddingInstanceIterator
validate(Instances) - Method in class weka.dl4j.iterators.instance.sequence.text.rnn.RnnTextFilesEmbeddingInstanceIterator: Validates the input dataset
valueAt(int, int) - Method in class weka.dl4j.schedules.ConstantSchedule.ConstantScheduleImpl
valueOf(String) - Static method in enum weka.core.LogConfiguration.LogLevel: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.AlgoMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.CacheMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.ConvolutionMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.GradientNormalization: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.PoolingType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.enums.PretrainedType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.inference.ClassmapType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.schedules.ScheduleType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.Dl4jDarknet19.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.DenseNet.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.EfficientNet.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.InceptionResNetV2.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.InceptionV3.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.MobileNet.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.NASNet.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.ResNet.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.VGG.VARIATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.dl4j.zoo.keras.Xception.VARIATION: Returns the enum constant of this type with the specified name.
values() - Static method in enum weka.core.LogConfiguration.LogLevel: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.AlgoMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.CacheMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.ConvolutionMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.GradientNormalization: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.PoolingType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.enums.PretrainedType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.inference.ClassmapType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.schedules.ScheduleType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.Dl4jDarknet19.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.DenseNet.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.EfficientNet.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.InceptionResNetV2.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.InceptionV3.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.MobileNet.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.NASNet.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.ResNet.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.VGG.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.dl4j.zoo.keras.Xception.VARIATION: Returns an array containing the constants of this enum type, in the order they are declared.
VGG - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of VGG.
VGG() - Constructor for class weka.dl4j.zoo.keras.VGG: Instantiate the model.
VGG.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.
VoidCallable - Interface in weka.dl4j: Simple callable interafce with no parameters and no return value (void).

W

WeightNoise - Class in weka.dl4j.weightnoise: Weight noise wrapper.
WeightNoise() - Constructor for class weka.dl4j.weightnoise.WeightNoise
weka.classifiers.functions - package weka.classifiers.functions
weka.core - package weka.core
weka.core.converters - package weka.core.converters
weka.core.progress - package weka.core.progress
weka.dl4j - package weka.dl4j
weka.dl4j.activations - package weka.dl4j.activations
weka.dl4j.distribution - package weka.dl4j.distribution
weka.dl4j.dropout - package weka.dl4j.dropout
weka.dl4j.earlystopping - package weka.dl4j.earlystopping
weka.dl4j.enums - package weka.dl4j.enums
weka.dl4j.inference - package weka.dl4j.inference
weka.dl4j.interpretability - package weka.dl4j.interpretability
weka.dl4j.interpretability.listeners - package weka.dl4j.interpretability.listeners
weka.dl4j.iterators.dataset - package weka.dl4j.iterators.dataset
weka.dl4j.iterators.dataset.sequence - package weka.dl4j.iterators.dataset.sequence
weka.dl4j.iterators.dataset.sequence.text.cnn - package weka.dl4j.iterators.dataset.sequence.text.cnn
weka.dl4j.iterators.dataset.sequence.text.rnn - package weka.dl4j.iterators.dataset.sequence.text.rnn
weka.dl4j.iterators.instance - package weka.dl4j.iterators.instance
weka.dl4j.iterators.instance.api - package weka.dl4j.iterators.instance.api
weka.dl4j.iterators.instance.sequence - package weka.dl4j.iterators.instance.sequence
weka.dl4j.iterators.instance.sequence.text - package weka.dl4j.iterators.instance.sequence.text
weka.dl4j.iterators.instance.sequence.text.cnn - package weka.dl4j.iterators.instance.sequence.text.cnn
weka.dl4j.iterators.instance.sequence.text.rnn - package weka.dl4j.iterators.instance.sequence.text.rnn
weka.dl4j.iterators.provider - package weka.dl4j.iterators.provider
weka.dl4j.layers - package weka.dl4j.layers
weka.dl4j.layers.lambda - package weka.dl4j.layers.lambda
weka.dl4j.listener - package weka.dl4j.listener
weka.dl4j.lossfunctions - package weka.dl4j.lossfunctions
weka.dl4j.schedules - package weka.dl4j.schedules
weka.dl4j.scripts.keras_downloading - package weka.dl4j.scripts.keras_downloading
weka.dl4j.stepfunctions - package weka.dl4j.stepfunctions
weka.dl4j.text.sentenceiterator - package weka.dl4j.text.sentenceiterator
weka.dl4j.text.stopwords - package weka.dl4j.text.stopwords
weka.dl4j.text.tokenization.preprocessor - package weka.dl4j.text.tokenization.preprocessor
weka.dl4j.text.tokenization.preprocessor.impl - package weka.dl4j.text.tokenization.preprocessor.impl
weka.dl4j.text.tokenization.tokenizer - package weka.dl4j.text.tokenization.tokenizer
weka.dl4j.text.tokenization.tokenizer.factory - package weka.dl4j.text.tokenization.tokenizer.factory
weka.dl4j.text.tokenization.tokenizer.factory.impl - package weka.dl4j.text.tokenization.tokenizer.factory.impl
weka.dl4j.updater - package weka.dl4j.updater
weka.dl4j.weightnoise - package weka.dl4j.weightnoise
weka.dl4j.zoo - package weka.dl4j.zoo
weka.dl4j.zoo.keras - package weka.dl4j.zoo.keras
weka.examples - package weka.examples
weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute
weka.gui.explorer - package weka.gui.explorer
WekaDeeplearning4jExamples - Class in weka.examples
WekaDeeplearning4jExamples() - Constructor for class weka.examples.WekaDeeplearning4jExamples
WekaInstanceSentenceIterator - Class in weka.dl4j.text.sentenceiterator: A Deeplearning4j's sentence iterator for Weka Instances.
WekaInstanceSentenceIterator(Instances, int) - Constructor for class weka.dl4j.text.sentenceiterator.WekaInstanceSentenceIterator: initializes the Object
WekaScoreCAM - Class in weka.dl4j.interpretability: WEKA Wrapper for the Deeplearning4j ScoreCAM implementation.
WekaScoreCAM() - Constructor for class weka.dl4j.interpretability.WekaScoreCAM
WekaTokenizer - Class in weka.dl4j.text.tokenization.tokenizer: A DeepLearning4j's Tokenizer interface to Weka Tokenizer.
WekaTokenizer(String, Tokenizer) - Constructor for class weka.dl4j.text.tokenization.tokenizer.WekaTokenizer: initializes the Object
Word2VecLoader - Class in weka.core.converters: Loads Word2Vec seriliazed embeddings into Weka.
Word2VecLoader() - Constructor for class weka.core.converters.Word2VecLoader
wordVectors - Variable in class weka.dl4j.iterators.instance.sequence.text.AbstractTextEmbeddingIterator: Loaded word vectors
WORKSPACE_MODE - Static variable in class weka.dl4j.Preferences: Global workspace mode
WrongIteratorException - Exception in weka.core: Exception raised in the case of a wrong iterator
WrongIteratorException(String) - Constructor for exception weka.core.WrongIteratorException
WrongIteratorException(String, Throwable) - Constructor for exception weka.core.WrongIteratorException

X

Xception - Class in weka.dl4j.zoo.keras: Wrapper class for the different versions of Xception.
Xception() - Constructor for class weka.dl4j.zoo.keras.Xception: Instantiate the model.
Xception.VARIATION - Enum in weka.dl4j.zoo.keras: Different variations of the model.

Z

ZeroPaddingLayer - Class in weka.dl4j.layers: A version of DeepLearning4j's ZeroPaddingLayer layer that implements WEKA option handling.
ZeroPaddingLayer() - Constructor for class weka.dl4j.layers.ZeroPaddingLayer: Constructor for setting some defaults.

A B C D E F G H I K L M N O P R S T U V W X Z