Package | Description |
---|---|
org.nd4j.linalg.dataset | |
org.nd4j.linalg.dataset.api | |
org.nd4j.linalg.dataset.api.preprocessor | |
org.nd4j.linalg.heartbeat.utils |
Modifier and Type | Class and Description |
---|---|
class |
DataSet
A data transform (example/outcome pairs)
The outcomes are specifically for neural network encoding such that
any labels that are considered true are 1s.
|
Modifier and Type | Method and Description |
---|---|
DataSet |
DataSet.getRange(int from,
int to) |
Modifier and Type | Method and Description |
---|---|
DistributionStats.Builder |
DistributionStats.Builder.addFeatures(DataSet dataSet)
Add the features of a DataSet to the statistics
|
DistributionStats.Builder |
DistributionStats.Builder.addLabels(DataSet dataSet)
Add the labels of a DataSet to the statistics
|
Modifier and Type | Method and Description |
---|---|
DataSet |
DataSet.getRange(int from,
int to) |
Modifier and Type | Method and Description |
---|---|
void |
DataSetPreProcessor.preProcess(DataSet toPreProcess)
Pre process a dataset
|
static INDArray |
DataSetUtil.tailor2d(DataSet dataSet,
boolean areFeatures) |
static INDArray |
DataSetUtil.tailor3d2d(DataSet dataset,
boolean areFeatures)
Deprecated.
|
static INDArray |
DataSetUtil.tailor4d2d(DataSet dataset,
boolean areFeatures) |
Modifier and Type | Method and Description |
---|---|
void |
NormalizerMinMaxScaler.fit(DataSet dataSet) |
void |
ImagePreProcessingScaler.fit(DataSet dataSet)
Fit a dataset (only compute
based on the statistics from this dataset0
|
void |
DataNormalization.fit(DataSet dataSet)
Fit a dataset (only compute
based on the statistics from this dataset0
|
void |
NormalizerStandardize.fit(DataSet dataSet)
Fit the given model with dataset
to calculate mean and std dev with
|
void |
NormalizerMinMaxScaler.preProcess(DataSet toPreProcess) |
void |
ImagePreProcessingScaler.preProcess(DataSet toPreProcess) |
void |
DataNormalization.preProcess(DataSet toPreProcess) |
void |
NormalizerStandardize.preProcess(DataSet toPreProcess) |
void |
NormalizerMinMaxScaler.revert(DataSet toPreProcess)
Revert the data to what it was before transform
|
void |
ImagePreProcessingScaler.revert(DataSet toRevert) |
void |
DataNormalization.revert(DataSet toRevert)
Undo (revert) the normalization applied by this DataNormalization instance (arrays are modified in-place)
|
void |
NormalizerStandardize.revert(DataSet data)
Revert the data to what it was before transform
|
void |
NormalizerMinMaxScaler.revertPreProcess(DataSet toPreProcess) |
void |
NormalizerMinMaxScaler.transform(DataSet toPreProcess)
Transform the data
|
void |
ImagePreProcessingScaler.transform(DataSet toPreProcess)
Transform the data
|
void |
DataNormalization.transform(DataSet toPreProcess)
Transform the dataset
|
void |
NormalizerStandardize.transform(DataSet toPreProcess)
Transform the given dataset
|
Modifier and Type | Method and Description |
---|---|
static Task |
TaskUtils.buildTask(DataSet dataSet) |
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