smile.math.kernel

Class HellingerKernel

java.lang.Object

smile.math.kernel.HellingerKernel

All Implemented Interfaces:

java.io.Serializable, java.util.function.ToDoubleBiFunction<double[],double[]>, MercerKernel<double[]>

public class HellingerKernel
extends java.lang.Object
implements MercerKernel<double[]>

The Hellinger kernel. The Hellinger distance is used to quantify the similarity between two probability distributions. It is a type of f-divergence. The Hellinger distance H(P, Q) on discrete distributions is equivalent to the Euclidean distance of the square root vectors. The Hellinger kernel is 1 - H²(P, Q), which is equivalent to the dot product of the square root vectors.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
HellingerKernel() Constructor.

Method Summary

Modifier and Type	Method and Description
double[]	hi() Returns the upper bound of hyperparameters.
double[]	hyperparameters() Returns the hyperparameters for tuning.
double	k(double[] x, double[] y) Kernel function.
double[]	kg(double[] x, double[] y) Computes the kernel and its gradient over hyperparameters.
double[]	lo() Returns the lower bound of hyperparameters.
LinearKernel	of(double[] params) Returns the same kind kernel with the new hyperparameters.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Methods inherited from interface smile.math.kernel.MercerKernel

apply, applyAsDouble, K, K, KG

Constructor Detail

HellingerKernel

public HellingerKernel()

Constructor.

Method Detail

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

k

public double k(double[] x,
                double[] y)

Description copied from interface: MercerKernel

Kernel function.

Specified by:

k in interface MercerKernel<double[]>

kg

public double[] kg(double[] x,
                   double[] y)

Description copied from interface: MercerKernel

Computes the kernel and its gradient over hyperparameters.

Specified by:

kg in interface MercerKernel<double[]>

of

public LinearKernel of(double[] params)

Description copied from interface: MercerKernel

Returns the same kind kernel with the new hyperparameters.

Specified by:

of in interface MercerKernel<double[]>

hyperparameters

public double[] hyperparameters()

Description copied from interface: MercerKernel

Returns the hyperparameters for tuning.

Specified by:

hyperparameters in interface MercerKernel<double[]>

lo

public double[] lo()

Description copied from interface: MercerKernel

Returns the lower bound of hyperparameters.

Specified by:

lo in interface MercerKernel<double[]>

hi

public double[] hi()

Description copied from interface: MercerKernel

Returns the upper bound of hyperparameters.

Specified by:

hi in interface MercerKernel<double[]>