Documentation of 'jsat.distributions.empirical.kernelfunc.KernelFunction' Java class
KernelFunction
jsat.distributions.empirical.kernelfunc

Interface KernelFunction

  • All Superinterfaces:
    java.io.Serializable
    All Known Implementing Classes:
    BiweightKF, EpanechnikovKF, GaussKF, TriweightKF, UniformKF


    public interface KernelFunction
    extends java.io.Serializable
    Class for representing one dimensional kernel functions. Since they require no parameters and have no need for duplication, its is advised to make them singletons. See http://en.wikipedia.org/wiki/Kernel_(statistics)
    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method and Description
      double cutOff()
      As the value of |u| for the kernel function approaches infinity, the value of k(u) approaches zero.
      double intK(double u)
      Computes the value of the finite integral from -Infinity up to the value u, of the function given by k(double)
      double k(double u)
      Returns the weight to be applied to a sample for the normalized distance of two data points.
      double k2()
      Returns the variance of the kernel function
      double kPrime(double u)
      Returns the value of the derivative at a point, k'(u)
      java.lang.String toString()
      Returns the name of this kernel function
    • Method Detail

      • k

        double k(double u)
        Returns the weight to be applied to a sample for the normalized distance of two data points.
        Parameters:
        u - the distance of the data points
        Returns:
        the value in [0, 1) of the amount of weight to give to the sample based on its distance
      • intK

        double intK(double u)
        Computes the value of the finite integral from -Infinity up to the value u, of the function given by k(double)
        Parameters:
        u - the distance of the data points
        Returns:
        the value of the integration
      • kPrime

        double kPrime(double u)
        Returns the value of the derivative at a point, k'(u)
        Parameters:
        u - the distance of the data points
        Returns:
        the value of the derivative at u
      • k2

        double k2()
        Returns the variance of the kernel function
        Returns:
        the variance of the kernel function
      • cutOff

        double cutOff()
        As the value of |u| for the kernel function approaches infinity, the value of k(u) approaches zero. This function returns the minimal absolute value of u for which k(u) returns 0
        Returns:
        the first value for which k(u) = 0
      • toString

        java.lang.String toString()
        Returns the name of this kernel function
        Overrides:
        toString in class java.lang.Object
        Returns:
        the name of this kernel function

DataMelt 3.0 © DataMelt by jWork.ORG

You see the box below because you did not login.