Uses of Interface
org.nd4j.linalg.dataset.api.MultiDataSet

Packages that use MultiDataSet

Package	Description
org.nd4j.linalg.dataset
org.nd4j.linalg.dataset.api
org.nd4j.linalg.dataset.api.iterator
org.nd4j.linalg.dataset.api.preprocessor
org.nd4j.linalg.dataset.api.preprocessor.classimbalance

Uses of MultiDataSet in org.nd4j.linalg.dataset

Classes in org.nd4j.linalg.dataset that implement MultiDataSet

Modifier and Type	Class and Description
class	MultiDataSet Implementation of MultiDataSet

Methods in org.nd4j.linalg.dataset that return types with arguments of type MultiDataSet

Modifier and Type	Method and Description
List<MultiDataSet>	MultiDataSet.asList()

Method parameters in org.nd4j.linalg.dataset with type arguments of type MultiDataSet

Modifier and Type	Method and Description
static MultiDataSet	MultiDataSet.merge(Collection<? extends MultiDataSet> toMerge) Merge a collection of MultiDataSet objects into a single MultiDataSet.

Uses of MultiDataSet in org.nd4j.linalg.dataset.api

Methods in org.nd4j.linalg.dataset.api that return MultiDataSet

Modifier and Type	Method and Description
MultiDataSet	MultiDataSet.copy() Clone the dataset

Methods in org.nd4j.linalg.dataset.api that return types with arguments of type MultiDataSet

Modifier and Type	Method and Description
List<MultiDataSet>	MultiDataSet.asList() SplitV the MultiDataSet into a list of individual examples.

Methods in org.nd4j.linalg.dataset.api with parameters of type MultiDataSet

Modifier and Type	Method and Description
void	MultiDataSetPreProcessor.preProcess(MultiDataSet multiDataSet) Preprocess the MultiDataSet

Uses of MultiDataSet in org.nd4j.linalg.dataset.api.iterator

Methods in org.nd4j.linalg.dataset.api.iterator that return MultiDataSet

Modifier and Type	Method and Description
MultiDataSet	TestMultiDataSetIterator.next()
MultiDataSet	TestMultiDataSetIterator.next(int num)
MultiDataSet	MultiDataSetIterator.next(int num) Fetch the next 'num' examples.
MultiDataSet	ParallelMultiDataSetIterator.nextFor() Returns next DataSet for attached consumer
MultiDataSet	ParallelMultiDataSetIterator.nextFor(int consumer) Returns next DataSet for given consumer

Constructors in org.nd4j.linalg.dataset.api.iterator with parameters of type MultiDataSet

Constructor and Description
TestMultiDataSetIterator(int batch, MultiDataSet... dataset) Makes an iterator from the given datasets.

Uses of MultiDataSet in org.nd4j.linalg.dataset.api.preprocessor

Methods in org.nd4j.linalg.dataset.api.preprocessor with parameters of type MultiDataSet

Modifier and Type	Method and Description
void	MultiNormalizerHybrid.fit(MultiDataSet dataSet) Fit a MultiDataSet (only compute based on the statistics from this dataset)
void	AbstractMultiDataSetNormalizer.fit(MultiDataSet dataSet) Fit a MultiDataSet (only compute based on the statistics from this MultiDataSet)
void	ImageMultiPreProcessingScaler.fit(MultiDataSet dataSet)
void	CompositeMultiDataSetPreProcessor.preProcess(MultiDataSet multiDataSet)
void	MultiNormalizerHybrid.preProcess(MultiDataSet data)
void	MultiDataNormalization.preProcess(MultiDataSet multiDataSet)
void	AbstractMultiDataSetNormalizer.preProcess(MultiDataSet toPreProcess) Pre process a MultiDataSet
void	ImageMultiPreProcessingScaler.preProcess(MultiDataSet multiDataSet)
void	MultiNormalizerHybrid.revert(MultiDataSet data) Undo (revert) the normalization applied by this DataNormalization instance (arrays are modified in-place)
void	AbstractMultiDataSetNormalizer.revert(MultiDataSet data) Revert the data to what it was before transform
void	ImageMultiPreProcessingScaler.revert(MultiDataSet toRevert)
void	MultiNormalizerHybrid.transform(MultiDataSet data) Transform the dataset
void	AbstractMultiDataSetNormalizer.transform(MultiDataSet toPreProcess)
void	ImageMultiPreProcessingScaler.transform(MultiDataSet toPreProcess)

Uses of MultiDataSet in org.nd4j.linalg.dataset.api.preprocessor.classimbalance

Methods in org.nd4j.linalg.dataset.api.preprocessor.classimbalance with parameters of type MultiDataSet

Modifier and Type	Method and Description
void	UnderSamplingByMaskingMultiDataSetPreProcessor.preProcess(MultiDataSet multiDataSet)