weka.dl4j.iterators.instance

Class DefaultInstanceIterator

java.lang.Object

weka.dl4j.iterators.instance.AbstractInstanceIterator

weka.dl4j.iterators.instance.DefaultInstanceIterator

All Implemented Interfaces:

java.io.Serializable, weka.core.OptionHandler

Direct Known Subclasses:

ConvolutionInstanceIterator

public class DefaultInstanceIterator
extends AbstractInstanceIterator

Converts the given Instances object into a DataSet and then constructs and returns a DefaultDataSetIterator.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
DefaultInstanceIterator()

Method Summary

Modifier and Type	Method and Description
org.nd4j.linalg.dataset.api.iterator.DataSetIterator	getDataSetIterator(weka.core.Instances data, int seed, int batchSize) Returns the actual iterator.
java.lang.String[]	getOptions() Gets the current settings of the Classifier.
java.lang.String	globalInfo()
java.util.Enumeration<weka.core.Option>	listOptions() Returns an enumeration describing the available options.
void	setOptions(java.lang.String[] options) Parses a given list of options.
void	validate(weka.core.Instances data) Validates the input dataset

Methods inherited from class weka.dl4j.iterators.instance.AbstractInstanceIterator

getDataSetIterator, getTrainBatchSize, initialize, setTrainBatchSize

Methods inherited from class java.lang.Object

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

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

DefaultInstanceIterator

public DefaultInstanceIterator()

Method Detail

validate

public void validate(weka.core.Instances data)
              throws InvalidInputDataException

Description copied from class: AbstractInstanceIterator

Validates the input dataset

Specified by:

validate in class AbstractInstanceIterator

Parameters:

data - the input dataset

Throws:

InvalidInputDataException - if validation is unsuccessful

getDataSetIterator

public org.nd4j.linalg.dataset.api.iterator.DataSetIterator getDataSetIterator(weka.core.Instances data,
                                                                               int seed,
                                                                               int batchSize)
                                                                        throws InvalidInputDataException

Returns the actual iterator.

Specified by:

getDataSetIterator in class AbstractInstanceIterator

Parameters:

data - the dataset to use

seed - the seed for the random number generator

batchSize - the batch size to use

Returns:

the DataSetIterator

Throws:

InvalidInputDataException

globalInfo

public java.lang.String globalInfo()

listOptions

public java.util.Enumeration<weka.core.Option> listOptions()

Returns an enumeration describing the available options.

Specified by:

listOptions in interface weka.core.OptionHandler

Overrides:

listOptions in class AbstractInstanceIterator

Returns:

an enumeration of all the available options.

getOptions

public java.lang.String[] getOptions()

Gets the current settings of the Classifier.

Specified by:

getOptions in interface weka.core.OptionHandler

Overrides:

getOptions in class AbstractInstanceIterator

Returns:

an array of strings suitable for passing to setOptions

setOptions

public void setOptions(java.lang.String[] options)
                throws java.lang.Exception

Parses a given list of options.

Specified by:

setOptions in interface weka.core.OptionHandler

Overrides:

setOptions in class AbstractInstanceIterator

Parameters:

options - the list of options as an array of strings

Throws:

java.lang.Exception - if an option is not supported