Package smile.math.kernel

Class HellingerKernel

java.lang.Object
smile.math.kernel.HellingerKernel
All Implemented Interfaces:
Serializable, ToDoubleBiFunction<double[],double[]>, MercerKernel<double[]>
public class HellingerKernel extends 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:

  • Constructor Summary

    Constructors
    Constructor
    Description
    HellingerKernel()
    Constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    double[]
    hi()
    Returns the upper bound of hyperparameters (in hyperparameter tuning).
    double[]
    hyperparameters()
    Returns the hyperparameters of kernel.
    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 (in hyperparameter tuning).
    LinearKernel
    of(double[] params)
    Returns the same kind kernel with the new hyperparameters.
    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 Details

    • HellingerKernel

      public HellingerKernel()
      Constructor.

  • Method Details

    • toString

      public String toString()
      Overrides:
      toString in class Object

    • k

      public double k(double[] x, double[] y)
      Description copied from interface: MercerKernel
      Kernel function.
      Specified by:
      k in interface MercerKernel<double[]>
      Parameters:
      x - an object.
      y - an object.
      Returns:
      the kernel value.

    • 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[]>
      Parameters:
      x - an object.
      y - an object.
      Returns:
      the kernel value and gradient.

    • 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[]>
      Parameters:
      params - the hyperparameters.
      Returns:
      the same kind kernel with the new hyperparameters.

    • hyperparameters

      public double[] hyperparameters()
      Description copied from interface: MercerKernel
      Returns the hyperparameters of kernel.
      Specified by:
      hyperparameters in interface MercerKernel<double[]>
      Returns:
      the hyperparameters of kernel.

    • lo

      public double[] lo()
      Description copied from interface: MercerKernel
      Returns the lower bound of hyperparameters (in hyperparameter tuning).
      Specified by:
      lo in interface MercerKernel<double[]>
      Returns:
      the lower bound of hyperparameters.

    • hi

      public double[] hi()
      Description copied from interface: MercerKernel
      Returns the upper bound of hyperparameters (in hyperparameter tuning).
      Specified by:
      hi in interface MercerKernel<double[]>
      Returns:
      the upper bound of hyperparameters.