org.nd4j.linalg.dataset.api.preprocessor

Class NormalizerStandardize

java.lang.Object

org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize

All Implemented Interfaces:

DataSetPreProcessor

public class NormalizerStandardize
extends Object
implements DataSetPreProcessor

Standard scaler calculates a moving column wise variance and mean http://www.johndcook.com/blog/standard_deviation/

Constructor Summary

Constructors

Constructor and Description
NormalizerStandardize()

Method Summary

Modifier and Type	Method and Description
void	fit(DataSet dataSet) Fit the given model with dataset to calculate mean and std dev with
void	fit(DataSetIterator iterator) Fit the given model with a given iterator to calculate mean and std dev with
INDArray	getMean()
INDArray	getStd()
void	load(File mean, File std) Load the given mean and std
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 mean, File std) Save the current mean and std
void	transform(DataSet toPreProcess) Transform the given dataset
void	transform(DataSetIterator toPreProcessIter) Transform the dataset from given iterator Need not set preprocessor on the iterator in this case

Methods inherited from class java.lang.Object

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

Constructor Detail

NormalizerStandardize

public NormalizerStandardize()

Method Detail

fit

public void fit(DataSet dataSet)

Fit the given model with dataset to calculate mean and std dev with

Parameters:

dataset -

fit

public void fit(DataSetIterator iterator)

Fit the given model with a given iterator to calculate mean and std dev with

Parameters:

iterator -

preProcess

public void preProcess(DataSet toPreProcess)

Description copied from interface: DataSetPreProcessor

Pre process a dataset

Specified by:

preProcess in interface DataSetPreProcessor

Parameters:

toPreProcess - the data set to pre process

transform

public void transform(DataSet toPreProcess)

Transform the given dataset

Parameters:

toPreProcess -

transform

public void transform(DataSetIterator toPreProcessIter)

Transform the dataset from given iterator Need not set preprocessor on the iterator in this case

Parameters:

toPreProcess - the dataset to transform

revertPreProcess

public void revertPreProcess(DataSet toPreProcess)

revert

public void revert(DataSet toPreProcess)

Revert the data to what it was before transform

Parameters:

toPreProcess - the dataset to revert back

revert

public void revert(DataSetIterator toPreProcessIter)

getMean

public INDArray getMean()

getStd

public INDArray getStd()

load

public void load(File mean,
                 File std)
          throws IOException

Load the given mean and std

Parameters:

mean - the mean file

std - the std file

Throws:

IOException

save

public void save(File mean,
                 File std)
          throws IOException

Save the current mean and std

Parameters:

mean - the mean

std - the std

Throws:

IOException