Package org.nd4j.linalg.dataset.api.preprocessor

Class NormalizerMinMaxScaler

java.lang.Object

org.nd4j.linalg.dataset.api.preprocessor.AbstractNormalizer

org.nd4j.linalg.dataset.api.preprocessor.AbstractDataSetNormalizer<MinMaxStats>

org.nd4j.linalg.dataset.api.preprocessor.NormalizerMinMaxScaler

All Implemented Interfaces:

Serializable, DataSetPreProcessor, DataNormalization, Normalizer<DataSet>

public class NormalizerMinMaxScaler
extends AbstractDataSetNormalizer<MinMaxStats>

See Also:

Serialized Form

Field Summary

Fields inherited from class org.nd4j.linalg.dataset.api.preprocessor.AbstractDataSetNormalizer

strategy

Constructor Summary

Constructors

Constructor	Description
NormalizerMinMaxScaler()
NormalizerMinMaxScaler(double minRange, double maxRange)	Preprocessor can take a range as minRange and maxRange

Method Summary

Modifier and Type	Method	Description
INDArray	getLabelMax()
INDArray	getLabelMin()
INDArray	getMax()
INDArray	getMin()
double	getTargetMax()
double	getTargetMin()
NormalizerType	getType()	Get the enum opType of this normalizer
void	load(File... statistics)	Load the given min and max
protected NormalizerStats.Builder	newBuilder()
void	save(File... files)	Deprecated. use instead
void	setFeatureStats(@NonNull INDArray featureMin, @NonNull INDArray featureMax)
void	setLabelStats(@NonNull INDArray labelMin, @NonNull INDArray labelMax)

Methods inherited from class org.nd4j.linalg.dataset.api.preprocessor.AbstractDataSetNormalizer

fit, fit, fitLabel, getFeatureStats, getLabelStats, isFit, isFitLabel, preProcess, revert, revertFeatures, revertFeatures, revertLabels, revertLabels, transform, transform, transform, transformLabel, transformLabel

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

NormalizerMinMaxScaler

public NormalizerMinMaxScaler()

NormalizerMinMaxScaler

public NormalizerMinMaxScaler(double minRange,
                              double maxRange)

Preprocessor can take a range as minRange and maxRange

Parameters:

minRange -

maxRange -

Method Detail

setFeatureStats

public void setFeatureStats(@NonNull
                            @NonNull INDArray featureMin,
                            @NonNull
                            @NonNull INDArray featureMax)

setLabelStats

public void setLabelStats(@NonNull
                          @NonNull INDArray labelMin,
                          @NonNull
                          @NonNull INDArray labelMax)

getTargetMin

public double getTargetMin()

getTargetMax

public double getTargetMax()

getMin

public INDArray getMin()

getMax

public INDArray getMax()

getLabelMin

public INDArray getLabelMin()

getLabelMax

public INDArray getLabelMax()

load

public void load(File... statistics)
          throws IOException

Load the given min and max

Parameters:

statistics - the statistics to load

Throws:

IOException

save

public void save(File... files)
          throws IOException

Deprecated.

use instead

Save the current min and max

Parameters:

files - the statistics to save

Throws:

IOException

newBuilder

protected NormalizerStats.Builder newBuilder()

Specified by:

newBuilder in class AbstractDataSetNormalizer<MinMaxStats>

getType

public NormalizerType getType()

Description copied from interface: Normalizer

Get the enum opType of this normalizer

Returns:

the opType

See Also:

NormalizerSerializerStrategy.getSupportedType()