be.ac.ulb.mlg.utils.measure
Class HilbertSchmidt

java.lang.Object
  be.ac.ulb.mlg.utils.measure.HilbertSchmidt

All Implemented Interfaces:

Measure

public class HilbertSchmidt
extends Object
implements Measure

Compute the Hilbert-Schmidt independence criterion according to the estimate in the paper "On Kernel Parameter Selection in Hilbert-Schmidt Independence Criterion" p.3

Field Summary

Fields inherited from interface be.ac.ulb.mlg.utils.Measure

ERROR_VALUE

Constructor Summary

HilbertSchmidt()
Initializing the Hilbert-Schmidt independence criterion to use the Gaussian Kernel

HilbertSchmidt(Kernel kernelA, Kernel kernelB)
Initializing the Hilbert-Schmidt independence criterion with specified kernels

Method Summary

boolean	hasNativeImplementation() Know if the measure owns a native implementation
double	measure(double[] A, double[] B, boolean[] computable) Compute the measure between two data vectors
static double	norm(double[] A, double[] B, boolean[] computable)
boolean	requireDataTransformation() Know if the measure need to transform input data (input data are copied to be preserved)
void	transform(double[][] data) The transformation method called before measurement

Methods inherited from class java.lang.Object

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

Constructor Detail

HilbertSchmidt

public HilbertSchmidt(Kernel kernelA,
                      Kernel kernelB)

Initializing the Hilbert-Schmidt independence criterion with specified kernels

Parameters:

kernelA - kernel for the first vector values

kernelA - kernel for the second vector values

HilbertSchmidt

public HilbertSchmidt()

Initializing the Hilbert-Schmidt independence criterion to use the Gaussian Kernel

Method Detail

measure

public double measure(double[] A,
                      double[] B,
                      boolean[] computable)

Description copied from interface: Measure

Compute the measure between two data vectors

Specified by:

measure in interface Measure

Parameters:

A - The first data vector

B - The second data vector

computable - Boolean vector set to true except for indexes they must be ignored during the measurement

Returns:

The measure between a and b

norm

public static double norm(double[] A,
                          double[] B,
                          boolean[] computable)

hasNativeImplementation

public boolean hasNativeImplementation()

Description copied from interface: Measure

Know if the measure owns a native implementation

Specified by:

hasNativeImplementation in interface Measure

Returns:

True if the measure is also natively implemented

requireDataTransformation

public boolean requireDataTransformation()

Description copied from interface: Measure

Know if the measure need to transform input data (input data are copied to be preserved)

Specified by:

requireDataTransformation in interface Measure

Returns:

True if the input data require some transformation

transform

public void transform(double[][] data)

Description copied from interface: Measure

The transformation method called before measurement

Specified by:

transform in interface Measure

Parameters:

data - An input data vector to be measured