public class NormalizerMinMaxScaler extends Object implements DataSetPreProcessor
| Constructor and Description |
|---|
NormalizerMinMaxScaler() |
NormalizerMinMaxScaler(double minRange,
double maxRange)
Preprocessor can take a range as minRange and maxRange
|
| Modifier and Type | Method and Description |
|---|---|
void |
fit(DataSet dataSet) |
void |
fit(DataSetIterator iterator)
Fit the given model
|
INDArray |
getMax() |
INDArray |
getMin() |
void |
load(File min,
File max)
Load the given min and max
|
void |
preProcess(DataSet toPreProcess)
Pre process a dataset
|
void |
revert(DataSet toPreProcess)
Revert the data to what it was before transform
|
void |
revert(DataSetIterator toPreProcessIter) |
void |
revertPreProcess(DataSet toPreProcess) |
void |
save(File min,
File max)
Save the current min and max
|
void |
setMaxRange(double maxRange) |
void |
setMinRange(double minRange) |
void |
transform(DataSet toPreProcess)
Transform the data
|
void |
transform(DataSetIterator toPreProcessIter) |
public NormalizerMinMaxScaler(double minRange,
double maxRange)
minRange - maxRange - public NormalizerMinMaxScaler()
public void setMinRange(double minRange)
public void setMaxRange(double maxRange)
public void fit(DataSet dataSet)
public void fit(DataSetIterator iterator)
iterator - for the data to iterate overpublic void preProcess(DataSet toPreProcess)
DataSetPreProcessorpreProcess in interface DataSetPreProcessortoPreProcess - the data set to pre processpublic void transform(DataSet toPreProcess)
toPreProcess - the dataset to transformpublic void transform(DataSetIterator toPreProcessIter)
public void revertPreProcess(DataSet toPreProcess)
public void revert(DataSet toPreProcess)
toPreProcess - the dataset to revert backpublic void revert(DataSetIterator toPreProcessIter)
public INDArray getMin()
public INDArray getMax()
public void load(File min, File max) throws IOException
min - the min filemax - the max fileIOExceptionpublic void save(File min, File max) throws IOException
min - the minmax - the maxIOExceptionCopyright © 2016. All Rights Reserved.