Package | Description |
---|---|
org.nd4j.linalg.dataset | |
org.nd4j.linalg.dataset.api | |
org.nd4j.linalg.dataset.api.iterator | |
org.nd4j.linalg.dataset.api.preprocessor |
Modifier and Type | Class and Description |
---|---|
class |
MultiDataSet
Implementation of
MultiDataSet |
Modifier and Type | Method and Description |
---|---|
List<MultiDataSet> |
MultiDataSet.asList() |
Modifier and Type | Method and Description |
---|---|
static MultiDataSet |
MultiDataSet.merge(Collection<? extends MultiDataSet> toMerge)
Merge a collection of MultiDataSet objects into a single MultiDataSet.
|
Modifier and Type | Method and Description |
---|---|
MultiDataSet |
MultiDataSet.copy()
Clone the dataset
|
Modifier and Type | Method and Description |
---|---|
List<MultiDataSet> |
MultiDataSet.asList()
Split the MultiDataSet into a list of individual examples.
|
Modifier and Type | Method and Description |
---|---|
void |
MultiDataSetPreProcessor.preProcess(MultiDataSet multiDataSet)
Preprocess the 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.
|
Constructor and Description |
---|
TestMultiDataSetIterator(int batch,
MultiDataSet... dataset)
Makes an iterator from the given datasets.
|
Modifier and Type | Method and Description |
---|---|
void |
MultiNormalizerStandardize.fit(MultiDataSet dataSet)
Fit the model with a MultiDataSet to calculate means and standard deviations with
|
void |
MultiNormalizerStandardize.preProcess(MultiDataSet toPreProcess) |
void |
MultiNormalizerStandardize.revert(MultiDataSet data)
Revert the data to what it was before transform
|
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