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

A

AbstractDataSetIterator - Class in weka.dl4j.iterators

An abstract iterator wrapper.

AbstractDataSetIterator() - Constructor for class weka.dl4j.iterators.AbstractDataSetIterator

asyncSupported() - Method in class weka.dl4j.ShufflingDataSetIterator

Whether the iterator can be used asynchronously.

B

batch() - Method in class weka.dl4j.ShufflingDataSetIterator

The size of the mini batches.

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

Constructs binomial distribution with 1 trial and success probability 0.5.

buildClassifier(Instances) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

The method used to train the classifier.

C

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.

cursor() - Method in class weka.dl4j.ShufflingDataSetIterator

The cursor given the location in the dataset.

D

DefaultInstancesIterator - Class in weka.dl4j.iterators

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

DefaultInstancesIterator() - Constructor for class weka.dl4j.iterators.DefaultInstancesIterator

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.

distributionForInstance(Instance) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

The method to use when making predictions for a test instance.

Dl4jMlpClassifier - Class in weka.classifiers.functions

A wrapper for DeepLearning4j that can be used to train a multi-layer perceptron using that library.

Dl4jMlpClassifier() - Constructor for class weka.classifiers.functions.Dl4jMlpClassifier

E

EasyImageRecordReader - Class in weka.dl4j

ImageRecordReader in DeepLearning4j assumes that your images are separated into different folders, where each folder is a class, e.g.

EasyImageRecordReader(int, int, int, ArrayList<File>, ArrayList<String>, int) - Constructor for class weka.dl4j.EasyImageRecordReader

Constructor for the record reader.

F

FileIterationListener - Class in weka.dl4j

Class for listening to performance stats and writing them to a file.

FileIterationListener(String, int) - Constructor for class weka.dl4j.FileIterationListener

Constructor for this listener.

G

getActivationFunction() - Method in class weka.dl4j.layers.BatchNormalization

getActivationFunction() - Method in class weka.dl4j.layers.ConvolutionLayer

getActivationFunction() - Method in class weka.dl4j.layers.DenseLayer

getActivationFunction() - Method in class weka.dl4j.layers.OutputLayer

getActivationFunction() - Method in class weka.dl4j.layers.SubsamplingLayer

getAdamMeanDecay() - Method in class weka.dl4j.layers.BatchNormalization

getAdamMeanDecay() - Method in class weka.dl4j.layers.ConvolutionLayer

getAdamMeanDecay() - Method in class weka.dl4j.layers.DenseLayer

getAdamMeanDecay() - Method in class weka.dl4j.layers.OutputLayer

getAdamMeanDecay() - Method in class weka.dl4j.layers.SubsamplingLayer

getAdamVarDecay() - Method in class weka.dl4j.layers.BatchNormalization

getAdamVarDecay() - Method in class weka.dl4j.layers.ConvolutionLayer

getAdamVarDecay() - Method in class weka.dl4j.layers.DenseLayer

getAdamVarDecay() - Method in class weka.dl4j.layers.OutputLayer

getAdamVarDecay() - Method in class weka.dl4j.layers.SubsamplingLayer

getBeta() - Method in class weka.dl4j.layers.BatchNormalization

getBiasInit() - Method in class weka.dl4j.layers.BatchNormalization

getBiasInit() - Method in class weka.dl4j.layers.ConvolutionLayer

getBiasInit() - Method in class weka.dl4j.layers.DenseLayer

getBiasInit() - Method in class weka.dl4j.layers.OutputLayer

getBiasInit() - Method in class weka.dl4j.layers.SubsamplingLayer

getBiasL1() - Method in class weka.dl4j.layers.BatchNormalization

getBiasL1() - Method in class weka.dl4j.layers.ConvolutionLayer

getBiasL1() - Method in class weka.dl4j.layers.DenseLayer

getBiasL1() - Method in class weka.dl4j.layers.OutputLayer

getBiasL1() - Method in class weka.dl4j.layers.SubsamplingLayer

getBiasL2() - Method in class weka.dl4j.layers.BatchNormalization

getBiasL2() - Method in class weka.dl4j.layers.ConvolutionLayer

getBiasL2() - Method in class weka.dl4j.layers.DenseLayer

getBiasL2() - Method in class weka.dl4j.layers.OutputLayer

getBiasL2() - Method in class weka.dl4j.layers.SubsamplingLayer

getBiasLearningRate() - Method in class weka.dl4j.layers.BatchNormalization

getBiasLearningRate() - Method in class weka.dl4j.layers.ConvolutionLayer

getBiasLearningRate() - Method in class weka.dl4j.layers.DenseLayer

getBiasLearningRate() - Method in class weka.dl4j.layers.OutputLayer

getBiasLearningRate() - Method in class weka.dl4j.layers.SubsamplingLayer

getCapabilities() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

Returns default capabilities of the classifier.

getConvolutionMode() - Method in class weka.dl4j.layers.ConvolutionLayer

getCudnnAlgoMode() - Method in class weka.dl4j.layers.ConvolutionLayer

getDataSetIterator() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

getDecay() - Method in class weka.dl4j.layers.BatchNormalization

getDist() - Method in class weka.dl4j.layers.BatchNormalization

getDist() - Method in class weka.dl4j.layers.ConvolutionLayer

getDist() - Method in class weka.dl4j.layers.DenseLayer

getDist() - Method in class weka.dl4j.layers.OutputLayer

getDist() - Method in class weka.dl4j.layers.SubsamplingLayer

getDropOut() - Method in class weka.dl4j.layers.BatchNormalization

getDropOut() - Method in class weka.dl4j.layers.ConvolutionLayer

getDropOut() - Method in class weka.dl4j.layers.DenseLayer

getDropOut() - Method in class weka.dl4j.layers.OutputLayer

getDropOut() - Method in class weka.dl4j.layers.SubsamplingLayer

getEps() - Method in class weka.dl4j.layers.BatchNormalization

getEpsilon() - Method in class weka.dl4j.layers.BatchNormalization

getEpsilon() - Method in class weka.dl4j.layers.ConvolutionLayer

getEpsilon() - Method in class weka.dl4j.layers.DenseLayer

getEpsilon() - Method in class weka.dl4j.layers.OutputLayer

getEpsilon() - Method in class weka.dl4j.layers.SubsamplingLayer

getGamma() - Method in class weka.dl4j.layers.BatchNormalization

getGradientNormalization() - Method in class weka.dl4j.layers.BatchNormalization

getGradientNormalization() - Method in class weka.dl4j.layers.ConvolutionLayer

getGradientNormalization() - Method in class weka.dl4j.layers.DenseLayer

getGradientNormalization() - Method in class weka.dl4j.layers.OutputLayer

getGradientNormalization() - Method in class weka.dl4j.layers.SubsamplingLayer

getGradientNormalizationThreshold() - Method in class weka.dl4j.layers.BatchNormalization

getGradientNormalizationThreshold() - Method in class weka.dl4j.layers.ConvolutionLayer

getGradientNormalizationThreshold() - Method in class weka.dl4j.layers.DenseLayer

getGradientNormalizationThreshold() - Method in class weka.dl4j.layers.OutputLayer

getGradientNormalizationThreshold() - Method in class weka.dl4j.layers.SubsamplingLayer

getHeight() - Method in class weka.dl4j.iterators.ImageDataSetIterator

getImagesLocation() - Method in class weka.dl4j.iterators.ImageDataSetIterator

getIterator(Instances, int) - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Returns the actual iterator.

getIterator(Instances, int, int) - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Returns the actual iterator.

getIterator(Instances, int, int) - Method in class weka.dl4j.iterators.DefaultInstancesIterator

Returns the actual iterator.

getIterator(Instances, int, int) - Method in class weka.dl4j.iterators.ImageDataSetIterator

This method returns the iterator.

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.layers.BatchNormalization

getL1() - Method in class weka.dl4j.layers.ConvolutionLayer

getL1() - Method in class weka.dl4j.layers.DenseLayer

getL1() - Method in class weka.dl4j.layers.OutputLayer

getL1() - Method in class weka.dl4j.layers.SubsamplingLayer

getL2() - Method in class weka.dl4j.layers.BatchNormalization

getL2() - Method in class weka.dl4j.layers.ConvolutionLayer

getL2() - Method in class weka.dl4j.layers.DenseLayer

getL2() - Method in class weka.dl4j.layers.OutputLayer

getL2() - Method in class weka.dl4j.layers.SubsamplingLayer

getLabels() - Method in class weka.dl4j.ShufflingDataSetIterator

Gets the labels.

getLayerName() - Method in class weka.dl4j.layers.BatchNormalization

getLayerName() - Method in class weka.dl4j.layers.ConvolutionLayer

getLayerName() - Method in class weka.dl4j.layers.DenseLayer

getLayerName() - Method in class weka.dl4j.layers.OutputLayer

getLayerName() - Method in class weka.dl4j.layers.SubsamplingLayer

getLayers() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

getLearningRate() - Method in class weka.dl4j.layers.BatchNormalization

getLearningRate() - Method in class weka.dl4j.layers.ConvolutionLayer

getLearningRate() - Method in class weka.dl4j.layers.DenseLayer

getLearningRate() - Method in class weka.dl4j.layers.OutputLayer

getLearningRate() - Method in class weka.dl4j.layers.SubsamplingLayer

getLearningRateSchedule() - Method in class weka.dl4j.layers.BatchNormalization

getLearningRateSchedule() - Method in class weka.dl4j.layers.ConvolutionLayer

getLearningRateSchedule() - Method in class weka.dl4j.layers.DenseLayer

getLearningRateSchedule() - Method in class weka.dl4j.layers.OutputLayer

getLearningRateSchedule() - Method in class weka.dl4j.layers.SubsamplingLayer

getLogFile() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

Get the log file

getLossFn() - Method in class weka.dl4j.layers.OutputLayer

getLower() - Method in class weka.dl4j.distribution.UniformDistribution

getMean() - Method in class weka.dl4j.distribution.NormalDistribution

getMomentum() - Method in class weka.dl4j.layers.BatchNormalization

getMomentum() - Method in class weka.dl4j.layers.ConvolutionLayer

getMomentum() - Method in class weka.dl4j.layers.DenseLayer

getMomentum() - Method in class weka.dl4j.layers.OutputLayer

getMomentum() - Method in class weka.dl4j.layers.SubsamplingLayer

getMomentumSchedule() - Method in class weka.dl4j.layers.BatchNormalization

getMomentumSchedule() - Method in class weka.dl4j.layers.ConvolutionLayer

getMomentumSchedule() - Method in class weka.dl4j.layers.DenseLayer

getMomentumSchedule() - Method in class weka.dl4j.layers.OutputLayer

getMomentumSchedule() - Method in class weka.dl4j.layers.SubsamplingLayer

getNIn() - Method in class weka.dl4j.layers.BatchNormalization

getNIn() - Method in class weka.dl4j.layers.ConvolutionLayer

getNIn() - Method in class weka.dl4j.layers.DenseLayer

getNIn() - Method in class weka.dl4j.layers.OutputLayer

getNOut() - Method in class weka.dl4j.layers.BatchNormalization

getNOut() - Method in class weka.dl4j.layers.ConvolutionLayer

getNOut() - Method in class weka.dl4j.layers.DenseLayer

getNOut() - Method in class weka.dl4j.layers.OutputLayer

getNumAttributes(Instances) - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Get the number of predictor attributes for this iterator.

getNumAttributes(Instances) - Method in class weka.dl4j.iterators.DefaultInstancesIterator

Returns the number of predictor attributes for this dataset.

getNumAttributes(Instances) - Method in class weka.dl4j.iterators.ImageDataSetIterator

This just returns the number of channels.

getNumChannels() - Method in class weka.dl4j.iterators.ImageDataSetIterator

getNumEpochs() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

getOptimizationAlgorithm() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

getOptions() - Method in class weka.dl4j.distribution.BinomialDistribution

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.UniformDistribution

Gets the current settings of the Classifier.

getOptions() - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Gets the current settings of the Classifier.

getOptions() - Method in class weka.dl4j.iterators.ImageDataSetIterator

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.ConvolutionLayer

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.OutputLayer

Gets the current settings of the Classifier.

getOptions() - Method in class weka.dl4j.layers.SubsamplingLayer

Gets the current settings of the Classifier.

getPadding() - Method in class weka.dl4j.layers.ConvolutionLayer

getPadding() - Method in class weka.dl4j.layers.SubsamplingLayer

getPaddingX() - Method in class weka.dl4j.layers.ConvolutionLayer

getPaddingX() - Method in class weka.dl4j.layers.SubsamplingLayer

getPaddingY() - Method in class weka.dl4j.layers.ConvolutionLayer

getPaddingY() - Method in class weka.dl4j.layers.SubsamplingLayer

getPoolingType() - Method in class weka.dl4j.layers.SubsamplingLayer

getPreProcessor() - Method in class weka.dl4j.ShufflingDataSetIterator

Gets the preprocessor.

getProbabilityOfSuccess() - Method in class weka.dl4j.distribution.BinomialDistribution

getRho() - Method in class weka.dl4j.layers.BatchNormalization

getRho() - Method in class weka.dl4j.layers.ConvolutionLayer

getRho() - Method in class weka.dl4j.layers.DenseLayer

getRho() - Method in class weka.dl4j.layers.OutputLayer

getRho() - Method in class weka.dl4j.layers.SubsamplingLayer

getRmsDecay() - Method in class weka.dl4j.layers.BatchNormalization

getRmsDecay() - Method in class weka.dl4j.layers.ConvolutionLayer

getRmsDecay() - Method in class weka.dl4j.layers.DenseLayer

getRmsDecay() - Method in class weka.dl4j.layers.OutputLayer

getRmsDecay() - Method in class weka.dl4j.layers.SubsamplingLayer

getStd() - Method in class weka.dl4j.distribution.NormalDistribution

getStride() - Method in class weka.dl4j.layers.ConvolutionLayer

getStride() - Method in class weka.dl4j.layers.SubsamplingLayer

getStrideX() - Method in class weka.dl4j.layers.ConvolutionLayer

getStrideX() - Method in class weka.dl4j.layers.SubsamplingLayer

getStrideY() - Method in class weka.dl4j.layers.ConvolutionLayer

getStrideY() - Method in class weka.dl4j.layers.SubsamplingLayer

getTrainBatchSize() - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Getting the training batch size

getTrainBatchSize() - Method in class weka.dl4j.iterators.DefaultInstancesIterator

getTrainBatchSize() - Method in class weka.dl4j.iterators.ImageDataSetIterator

getUpdater() - Method in class weka.dl4j.layers.BatchNormalization

getUpdater() - Method in class weka.dl4j.layers.ConvolutionLayer

getUpdater() - Method in class weka.dl4j.layers.DenseLayer

getUpdater() - Method in class weka.dl4j.layers.OutputLayer

getUpdater() - Method in class weka.dl4j.layers.SubsamplingLayer

getUpper() - Method in class weka.dl4j.distribution.UniformDistribution

getWeightInit() - Method in class weka.dl4j.layers.BatchNormalization

getWeightInit() - Method in class weka.dl4j.layers.ConvolutionLayer

getWeightInit() - Method in class weka.dl4j.layers.DenseLayer

getWeightInit() - Method in class weka.dl4j.layers.OutputLayer

getWeightInit() - Method in class weka.dl4j.layers.SubsamplingLayer

getWidth() - Method in class weka.dl4j.iterators.ImageDataSetIterator

globalInfo() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

globalInfo() - Method in class weka.dl4j.layers.BatchNormalization

Global info.

globalInfo() - Method in class weka.dl4j.layers.ConvolutionLayer

Global info.

globalInfo() - Method in class weka.dl4j.layers.DenseLayer

Global info.

globalInfo() - Method in class weka.dl4j.layers.OutputLayer

Global info.

globalInfo() - Method in class weka.dl4j.layers.SubsamplingLayer

Global info.

H

hasNext() - Method in class weka.dl4j.ShufflingDataSetIterator

Whether another batch of data is still available.

I

ImageDataSetIterator - Class in weka.dl4j.iterators

An iterator that loads images.

ImageDataSetIterator() - Constructor for class weka.dl4j.iterators.ImageDataSetIterator

initialize(InputSplit) - Method in class weka.dl4j.EasyImageRecordReader

Initializes the iterators.

inputColumns() - Method in class weka.dl4j.ShufflingDataSetIterator

Returns the number of input columns.

instancesToDataSet(Instances) - Static method in class weka.classifiers.functions.dl4j.Utils

Converts a set of training instances to a DataSet.

instanceToINDArray(Instance) - Static method in class weka.classifiers.functions.dl4j.Utils

Converts an instance to an INDArray.

invoke() - Method in class weka.dl4j.FileIterationListener

No-op method.

invoked() - Method in class weka.dl4j.FileIterationListener

Always returns false.

iterationDone(Model, int) - Method in class weka.dl4j.FileIterationListener

Method that gets called when an iteration is done.

L

listOptions() - Method in class weka.dl4j.distribution.BinomialDistribution

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.UniformDistribution

Returns an enumeration describing the available options.

listOptions() - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Returns an enumeration describing the available options.

listOptions() - Method in class weka.dl4j.iterators.ImageDataSetIterator

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.ConvolutionLayer

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.OutputLayer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.dl4j.layers.SubsamplingLayer

Returns an enumeration describing the available options.

M

main(String[]) - Static method in class weka.classifiers.functions.Dl4jMlpClassifier

The main method for running this class.

N

next() - Method in class weka.dl4j.EasyImageRecordReader

Gets the next element

next() - Method in class weka.dl4j.ShufflingDataSetIterator

Returns the next mini batch of data.

next(int) - Method in class weka.dl4j.ShufflingDataSetIterator

Returns a batch of the given size

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

Constructions normal distribution with mean 0 and unit variance.

numExamples() - Method in class weka.dl4j.ShufflingDataSetIterator

The number of examples in the dataset.

O

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.

P

preProcess(DataSet) - Method in class weka.dl4j.ScaleImagePixelsPreProcessor

Divides all intensity values by 255.

R

record(URI, DataInputStream) - Method in class weka.dl4j.EasyImageRecordReader

A method that still needs to be implemented.

remove() - Method in class weka.dl4j.ShufflingDataSetIterator

Enables removing of a mini-batch.

reset() - Method in class weka.dl4j.EasyImageRecordReader

Resets the record reader.

reset() - Method in class weka.dl4j.ShufflingDataSetIterator

Resets the cursor.

resetSupported() - Method in class weka.dl4j.ShufflingDataSetIterator

Whether the iterator can be reset.

RNNinstancesToDataSet(Instances) - Static method in class weka.classifiers.functions.dl4j.Utils

Converts a set of training instances corresponding to a time series to a DataSet.

S

ScaleImagePixelsPreProcessor - Class in weka.dl4j

A simple preprocessor that divides all values in the dataset by 255.

ScaleImagePixelsPreProcessor() - Constructor for class weka.dl4j.ScaleImagePixelsPreProcessor

setActivationFunction(String) - Method in class weka.dl4j.layers.BatchNormalization

setActivationFunction(String) - Method in class weka.dl4j.layers.ConvolutionLayer

setActivationFunction(String) - Method in class weka.dl4j.layers.DenseLayer

setActivationFunction(String) - Method in class weka.dl4j.layers.OutputLayer

setActivationFunction(String) - Method in class weka.dl4j.layers.SubsamplingLayer

setAdamMeanDecay(double) - Method in class weka.dl4j.layers.BatchNormalization

setAdamMeanDecay(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setAdamMeanDecay(double) - Method in class weka.dl4j.layers.DenseLayer

setAdamMeanDecay(double) - Method in class weka.dl4j.layers.OutputLayer

setAdamMeanDecay(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setAdamVarDecay(double) - Method in class weka.dl4j.layers.BatchNormalization

setAdamVarDecay(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setAdamVarDecay(double) - Method in class weka.dl4j.layers.DenseLayer

setAdamVarDecay(double) - Method in class weka.dl4j.layers.OutputLayer

setAdamVarDecay(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setBeta(double) - Method in class weka.dl4j.layers.BatchNormalization

setBiasInit(double) - Method in class weka.dl4j.layers.BatchNormalization

setBiasInit(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setBiasInit(double) - Method in class weka.dl4j.layers.DenseLayer

setBiasInit(double) - Method in class weka.dl4j.layers.OutputLayer

setBiasInit(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setBiasL1(double) - Method in class weka.dl4j.layers.BatchNormalization

setBiasL1(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setBiasL1(double) - Method in class weka.dl4j.layers.DenseLayer

setBiasL1(double) - Method in class weka.dl4j.layers.OutputLayer

setBiasL1(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setBiasL2(double) - Method in class weka.dl4j.layers.BatchNormalization

setBiasL2(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setBiasL2(double) - Method in class weka.dl4j.layers.DenseLayer

setBiasL2(double) - Method in class weka.dl4j.layers.OutputLayer

setBiasL2(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setBiasLearningRate(double) - Method in class weka.dl4j.layers.BatchNormalization

setBiasLearningRate(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setBiasLearningRate(double) - Method in class weka.dl4j.layers.DenseLayer

setBiasLearningRate(double) - Method in class weka.dl4j.layers.OutputLayer

setBiasLearningRate(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setConvolutionMode(ConvolutionMode) - Method in class weka.dl4j.layers.ConvolutionLayer

setCudnnAlgoMode(ConvolutionLayer.AlgoMode) - Method in class weka.dl4j.layers.ConvolutionLayer

setDataSetIterator(AbstractDataSetIterator) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

setDecay(double) - Method in class weka.dl4j.layers.BatchNormalization

setDist(Distribution) - Method in class weka.dl4j.layers.BatchNormalization

setDist(Distribution) - Method in class weka.dl4j.layers.ConvolutionLayer

setDist(Distribution) - Method in class weka.dl4j.layers.DenseLayer

setDist(Distribution) - Method in class weka.dl4j.layers.OutputLayer

setDist(Distribution) - Method in class weka.dl4j.layers.SubsamplingLayer

setDropOut(double) - Method in class weka.dl4j.layers.BatchNormalization

setDropOut(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setDropOut(double) - Method in class weka.dl4j.layers.DenseLayer

setDropOut(double) - Method in class weka.dl4j.layers.OutputLayer

setDropOut(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setEps(double) - Method in class weka.dl4j.layers.BatchNormalization

setEpsilon(double) - Method in class weka.dl4j.layers.BatchNormalization

setEpsilon(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setEpsilon(double) - Method in class weka.dl4j.layers.DenseLayer

setEpsilon(double) - Method in class weka.dl4j.layers.OutputLayer

setEpsilon(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setFiles(URI[]) - Method in class weka.dl4j.SpecifiableFolderSplit

The list of files to process.

setGamma(double) - Method in class weka.dl4j.layers.BatchNormalization

setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.layers.BatchNormalization

setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.layers.ConvolutionLayer

setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.layers.DenseLayer

setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.layers.OutputLayer

setGradientNormalization(GradientNormalization) - Method in class weka.dl4j.layers.SubsamplingLayer

setGradientNormalizationThreshold(double) - Method in class weka.dl4j.layers.BatchNormalization

setGradientNormalizationThreshold(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setGradientNormalizationThreshold(double) - Method in class weka.dl4j.layers.DenseLayer

setGradientNormalizationThreshold(double) - Method in class weka.dl4j.layers.OutputLayer

setGradientNormalizationThreshold(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setHeight(int) - Method in class weka.dl4j.iterators.ImageDataSetIterator

setImagesLocation(File) - Method in class weka.dl4j.iterators.ImageDataSetIterator

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.layers.BatchNormalization

setL1(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setL1(double) - Method in class weka.dl4j.layers.DenseLayer

setL1(double) - Method in class weka.dl4j.layers.OutputLayer

setL1(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setL2(double) - Method in class weka.dl4j.layers.BatchNormalization

setL2(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setL2(double) - Method in class weka.dl4j.layers.DenseLayer

setL2(double) - Method in class weka.dl4j.layers.OutputLayer

setL2(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setLayerName(String) - Method in class weka.dl4j.layers.BatchNormalization

setLayerName(String) - Method in class weka.dl4j.layers.ConvolutionLayer

setLayerName(String) - Method in class weka.dl4j.layers.DenseLayer

setLayerName(String) - Method in class weka.dl4j.layers.OutputLayer

setLayerName(String) - Method in class weka.dl4j.layers.SubsamplingLayer

setLayers(Layer[]) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

setLearningRate(double) - Method in class weka.dl4j.layers.BatchNormalization

setLearningRate(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setLearningRate(double) - Method in class weka.dl4j.layers.DenseLayer

setLearningRate(double) - Method in class weka.dl4j.layers.OutputLayer

setLearningRate(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setLearningRateSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.BatchNormalization

setLearningRateSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.ConvolutionLayer

setLearningRateSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.DenseLayer

setLearningRateSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.OutputLayer

setLearningRateSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.SubsamplingLayer

setLength(int) - Method in class weka.dl4j.SpecifiableFolderSplit

The length.

setLogFile(File) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

Set the log file

setLossFn(ILossFunction) - Method in class weka.dl4j.layers.OutputLayer

setLower(double) - Method in class weka.dl4j.distribution.UniformDistribution

setMean(double) - Method in class weka.dl4j.distribution.NormalDistribution

setMomentum(double) - Method in class weka.dl4j.layers.BatchNormalization

setMomentum(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setMomentum(double) - Method in class weka.dl4j.layers.DenseLayer

setMomentum(double) - Method in class weka.dl4j.layers.OutputLayer

setMomentum(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setMomentumSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.BatchNormalization

setMomentumSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.ConvolutionLayer

setMomentumSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.DenseLayer

setMomentumSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.OutputLayer

setMomentumSchedule(Map<Integer, Double>) - Method in class weka.dl4j.layers.SubsamplingLayer

setNIn(int) - Method in class weka.dl4j.layers.BatchNormalization

setNIn(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setNIn(int) - Method in class weka.dl4j.layers.DenseLayer

setNIn(int) - Method in class weka.dl4j.layers.OutputLayer

setNOut(int) - Method in class weka.dl4j.layers.BatchNormalization

setNOut(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setNOut(int) - Method in class weka.dl4j.layers.DenseLayer

setNOut(int) - Method in class weka.dl4j.layers.OutputLayer

setNumChannels(int) - Method in class weka.dl4j.iterators.ImageDataSetIterator

setNumEpochs(int) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

setOptimizationAlgorithm(OptimizationAlgorithm) - Method in class weka.classifiers.functions.Dl4jMlpClassifier

setOptions(String[]) - Method in class weka.dl4j.distribution.BinomialDistribution

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.UniformDistribution

Parses a given list of options.

setOptions(String[]) - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Parses a given list of options.

setOptions(String[]) - Method in class weka.dl4j.iterators.ImageDataSetIterator

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.ConvolutionLayer

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.OutputLayer

Parses a given list of options.

setOptions(String[]) - Method in class weka.dl4j.layers.SubsamplingLayer

Parses a given list of options.

setPadding(int[]) - Method in class weka.dl4j.layers.ConvolutionLayer

setPadding(int[]) - Method in class weka.dl4j.layers.SubsamplingLayer

setPaddingX(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setPaddingX(int) - Method in class weka.dl4j.layers.SubsamplingLayer

setPaddingY(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setPaddingY(int) - Method in class weka.dl4j.layers.SubsamplingLayer

setPoolingType(SubsamplingLayer.PoolingType) - Method in class weka.dl4j.layers.SubsamplingLayer

setPreProcessor(DataSetPreProcessor) - Method in class weka.dl4j.ShufflingDataSetIterator

Sets the preprocessor.

setProbabilityOfSuccess(double) - Method in class weka.dl4j.distribution.BinomialDistribution

setRho(double) - Method in class weka.dl4j.layers.BatchNormalization

setRho(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setRho(double) - Method in class weka.dl4j.layers.DenseLayer

setRho(double) - Method in class weka.dl4j.layers.OutputLayer

setRho(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setRmsDecay(double) - Method in class weka.dl4j.layers.BatchNormalization

setRmsDecay(double) - Method in class weka.dl4j.layers.ConvolutionLayer

setRmsDecay(double) - Method in class weka.dl4j.layers.DenseLayer

setRmsDecay(double) - Method in class weka.dl4j.layers.OutputLayer

setRmsDecay(double) - Method in class weka.dl4j.layers.SubsamplingLayer

setStd(double) - Method in class weka.dl4j.distribution.NormalDistribution

setStride(int[]) - Method in class weka.dl4j.layers.ConvolutionLayer

setStride(int[]) - Method in class weka.dl4j.layers.SubsamplingLayer

setStrideX(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setStrideX(int) - Method in class weka.dl4j.layers.SubsamplingLayer

setStrideY(int) - Method in class weka.dl4j.layers.ConvolutionLayer

setStrideY(int) - Method in class weka.dl4j.layers.SubsamplingLayer

setTrainBatchSize(int) - Method in class weka.dl4j.iterators.AbstractDataSetIterator

Setting the training batch size

setTrainBatchSize(int) - Method in class weka.dl4j.iterators.DefaultInstancesIterator

setTrainBatchSize(int) - Method in class weka.dl4j.iterators.ImageDataSetIterator

setUpdater(Updater) - Method in class weka.dl4j.layers.BatchNormalization

setUpdater(Updater) - Method in class weka.dl4j.layers.ConvolutionLayer

setUpdater(Updater) - Method in class weka.dl4j.layers.DenseLayer

setUpdater(Updater) - Method in class weka.dl4j.layers.OutputLayer

setUpdater(Updater) - Method in class weka.dl4j.layers.SubsamplingLayer

setUpper(double) - Method in class weka.dl4j.distribution.UniformDistribution

setWeightInit(WeightInit) - Method in class weka.dl4j.layers.BatchNormalization

setWeightInit(WeightInit) - Method in class weka.dl4j.layers.ConvolutionLayer

setWeightInit(WeightInit) - Method in class weka.dl4j.layers.DenseLayer

setWeightInit(WeightInit) - Method in class weka.dl4j.layers.OutputLayer

setWeightInit(WeightInit) - Method in class weka.dl4j.layers.SubsamplingLayer

setWidth(int) - Method in class weka.dl4j.iterators.ImageDataSetIterator

ShufflingDataSetIterator - Class in weka.dl4j

An nd4j mini-batch iterator that shuffles the data whenever it is reset.

ShufflingDataSetIterator(DataSet, int, int) - Constructor for class weka.dl4j.ShufflingDataSetIterator

Constructs a new shuffling iterator.

SpecifiableFolderSplit - Class in weka.dl4j

A hacky override of FileSplit that lets you specify the files directly.

SpecifiableFolderSplit() - Constructor for class weka.dl4j.SpecifiableFolderSplit

The constructor.

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

toString() - Method in class weka.classifiers.functions.Dl4jMlpClassifier

Returns a string describing the model.

totalExamples() - Method in class weka.dl4j.ShufflingDataSetIterator

Returns the total number of examples in the dataset.

totalOutcomes() - Method in class weka.dl4j.ShufflingDataSetIterator

Returns the total number of labels.

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

Constructions normal distribution with lower limit -1 and upper limit 1.

Utils - Class in weka.classifiers.functions.dl4j

Utility routines for the Dl4jMlpClassifier

Utils() - Constructor for class weka.classifiers.functions.dl4j.Utils

V

validate(Instances) - Method in class weka.dl4j.iterators.ImageDataSetIterator

Validates the input dataset

W

weka.classifiers.functions - package weka.classifiers.functions

weka.classifiers.functions.dl4j - package weka.classifiers.functions.dl4j

weka.dl4j - package weka.dl4j

weka.dl4j.distribution - package weka.dl4j.distribution

weka.dl4j.iterators - package weka.dl4j.iterators

weka.dl4j.layers - package weka.dl4j.layers

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