| 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 |
|---|---|
DataSet |
DataSet.getRange(int from,
int to) |
| Modifier and Type | Method and Description |
|---|---|
void |
DataSetPreProcessor.preProcess(DataSet toPreProcess)
Pre process a dataset
|
| Modifier and Type | Method and Description |
|---|---|
void |
NormalizerMinMaxScaler.fit(DataSet dataSet) |
void |
NormalizerStandardize.fit(DataSet dataSet)
Fit the given model with dataset
to calculate mean and std dev with
|
void |
NormalizerMinMaxScaler.preProcess(DataSet toPreProcess) |
void |
NormalizerStandardize.preProcess(DataSet toPreProcess) |
void |
NormalizerMinMaxScaler.revert(DataSet toPreProcess)
Revert the data to what it was before transform
|
void |
NormalizerStandardize.revert(DataSet toPreProcess)
Revert the data to what it was before transform
|
void |
NormalizerMinMaxScaler.revertPreProcess(DataSet toPreProcess) |
void |
NormalizerStandardize.revertPreProcess(DataSet toPreProcess) |
void |
NormalizerMinMaxScaler.transform(DataSet toPreProcess)
Transform the data
|
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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