weka.classifiers.functions

Class RnnSequenceClassifier

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.RandomizableClassifier

weka.classifiers.functions.Dl4jMlpClassifier

weka.classifiers.functions.RnnSequenceClassifier

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.classifiers.IterativeClassifier, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.OptionHandler, weka.core.Randomizable, weka.core.RevisionHandler

public class RnnSequenceClassifier
extends Dl4jMlpClassifier
implements weka.core.CapabilitiesHandler, weka.classifiers.Classifier, java.io.Serializable, weka.core.OptionHandler

A classifier that can handle sequences.

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.functions.Dl4jMlpClassifier

FILTER_NONE, FILTER_NORMALIZE, FILTER_STANDARDIZE, TAGS_FILTER

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
RnnSequenceClassifier()

Method Summary

Modifier and Type	Method and Description
double[]	distributionForInstance(weka.core.Instance instance) The method to use when making a prediction for a test instance.
double[][]	distributionsForInstances(weka.core.Instances insts) The method to use when making predictions for test instances.
weka.core.Capabilities	getCapabilities() Returns default capabilities of the classifier.
int	gettBPTTbackwardLength()
int	gettBPTTforwardLength()
AbstractZooModel	getZooModel() Deprecated.
java.lang.String	globalInfo() .
void	initializeClassifier(weka.core.Instances data) The method used to initialize the classifier.
void	settBPTTbackwardLength(int tBPTTbackwardLength)
void	settBPTTforwardLength(int tBPTTforwardLength)
void	setZooModel(AbstractZooModel zooModel) Deprecated.

Methods inherited from class weka.classifiers.functions.Dl4jMlpClassifier

arithmeticUnderflow, buildClassifier, done, featurizeForLayer, getActivationsAtLayers, getActivationsAtLayers, getCacheMode, getDoNotClearFilesystemCache, getEarlyStopping, getFilterType, getInputShape, getInstanceIterator, getIterationListener, getLayers, getLoadLayerSpecification, getLogConfig, getModel, getModelName, getNeuralNetConfiguration, getNumEpochs, getNumGPUs, getParameterAveragingFrequency, getPrefetchBufferSize, getQueueSize, getResume, implementsMoreEfficientBatchPrediction, isFilterMode, isValidOutputLayer, loadInferenceModel, loadModel, loadZooModelNoData, main, next, outputSingle, setCacheMode, setDoNotClearFilesystemCache, setEarlyStopping, setFilterMode, setFilterType, setInstanceIterator, setIterationListener, setLayers, setLoadLayerSpecification, setLogConfig, setNeuralNetConfiguration, setNumEpochs, setNumGPUs, setParameterAveragingFrequency, setPrefetchBufferSize, setQueueSize, setResume, splitTrainVal, toString, tryLoadFromFile, useEarlyStopping, useZooModel

Methods inherited from class weka.classifiers.RandomizableClassifier

getOptions, getSeed, listOptions, seedTipText, setOptions, setSeed

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.classifiers.Classifier

buildClassifier, classifyInstance

Methods inherited from interface weka.core.OptionHandler

getOptions, listOptions, makeCopy, setOptions

Methods inherited from interface weka.core.BatchPredictor

getBatchSize, setBatchSize

Constructor Detail

RnnSequenceClassifier

public RnnSequenceClassifier()

Method Detail

initializeClassifier

public void initializeClassifier(weka.core.Instances data)
                          throws java.lang.Exception

The method used to initialize the classifier.

Specified by:

initializeClassifier in interface weka.classifiers.IterativeClassifier

Overrides:

initializeClassifier in class Dl4jMlpClassifier

Parameters:

data - set of instances serving as training data

Throws:

java.lang.Exception - if something goes wrong in the training process

distributionsForInstances

public double[][] distributionsForInstances(weka.core.Instances insts)
                                     throws java.lang.Exception

The method to use when making predictions for test instances.

Specified by:

distributionsForInstances in interface weka.core.BatchPredictor

Overrides:

distributionsForInstances in class Dl4jMlpClassifier

Parameters:

insts - the instances to get predictions for

Returns:

the class probability estimates (if the class is nominal) or the numeric predictions (if it is numeric)

Throws:

java.lang.Exception - if something goes wrong at prediction time

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws java.lang.Exception

Description copied from class: Dl4jMlpClassifier

The method to use when making a prediction for a test instance. Use distributionsForInstances() instead for speed if possible.

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class Dl4jMlpClassifier

Parameters:

instance - the instance to get a prediction for

Returns:

the class probability estimates (if the class is nominal) or the numeric prediction (if it is numeric)

Throws:

java.lang.Exception - if something goes wrong at prediction time

gettBPTTbackwardLength

@OptionMetadata(description="Number of backpropagations through time backward (default = 25).",
                displayName="truncated backprop through time backward",
                commandLineParamName="tBPTTBackward",
                commandLineParamSynopsis="-tBPTTBackward <int>",
                displayOrder=20)
public int gettBPTTbackwardLength()

settBPTTbackwardLength

public void settBPTTbackwardLength(int tBPTTbackwardLength)

gettBPTTforwardLength

@OptionMetadata(description="Number of backpropagations through time forward (default = 25).",
                displayName="truncated backprop through time forward",
                commandLineParamName="tBPTTForward",
                commandLineParamSynopsis="-tBPTTForward <int>",
                displayOrder=21)
public int gettBPTTforwardLength()

settBPTTforwardLength

public void settBPTTforwardLength(int tBPTTforwardLength)

getZooModel

@Deprecated
 @ProgrammaticProperty
public AbstractZooModel getZooModel()

Deprecated.

Description copied from class: Dl4jMlpClassifier

Get the modelzoo model

Overrides:

getZooModel in class Dl4jMlpClassifier

Returns:

The modelzoo model object

setZooModel

@Deprecated
 @ProgrammaticProperty
public void setZooModel(AbstractZooModel zooModel)

Deprecated.

Description copied from class: Dl4jMlpClassifier

Set the modelzoo zooModel

Overrides:

setZooModel in class Dl4jMlpClassifier

Parameters:

zooModel - The predefined zooModel

getCapabilities

public weka.core.Capabilities getCapabilities()

Returns default capabilities of the classifier.

Specified by:

getCapabilities in interface weka.classifiers.Classifier

Specified by:

getCapabilities in interface weka.core.CapabilitiesHandler

Overrides:

getCapabilities in class Dl4jMlpClassifier

Returns:

the capabilities of this classifier

globalInfo

public java.lang.String globalInfo()

Description copied from class: Dl4jMlpClassifier

.

Overrides:

globalInfo in class Dl4jMlpClassifier

Returns:

Global info to return.