org.openimaj.math.statistics.normalisation

Class PerExampleMeanCenterVar

java.lang.Object

org.openimaj.math.statistics.normalisation.PerExampleMeanCenterVar

All Implemented Interfaces:

Normaliser

public class PerExampleMeanCenterVar
extends Object
implements Normaliser

Subtract the mean of each example vector from itself and divide by the standard deviation to normalise the vector such that it has unit variance. A regularisation term can be optionally included in the divisor.

Only use if the data is stationary (i.e., the statistics for each data dimension follow the same distribution).

Author:

Jonathon Hare (jsh2@ecs.soton.ac.uk)

Constructor Summary

Constructors

Constructor and Description
PerExampleMeanCenterVar(double eps) Construct with the given variance regularisation term.

Method Summary

Modifier and Type	Method and Description
double[]	normalise(double[] vector) Normalise the vector.
double[][]	normalise(double[][] data) Normalise the data.

Methods inherited from class java.lang.Object

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

Constructor Detail

PerExampleMeanCenterVar

public PerExampleMeanCenterVar(double eps)

Construct with the given variance regularisation term. Setting to zero disables the regulariser.

Parameters:

eps - the variance normalisation regularizer (each dimension is divided by sqrt(var + eps).

Method Detail

normalise

public double[] normalise(double[] vector)

Description copied from interface: Normaliser

Normalise the vector.

Specified by:

normalise in interface Normaliser

Parameters:

vector - the vector

Returns:

the normalised vector

normalise

public double[][] normalise(double[][] data)

Description copied from interface: Normaliser

Normalise the data.

Specified by:

normalise in interface Normaliser

Parameters:

data - the data (one vector per row)

Returns:

the normalised data