Package weka.estimators

Class MultivariateGaussianEstimator

java.lang.Object
weka.estimators.MultivariateGaussianEstimator
All Implemented Interfaces:
Serializable, MultivariateEstimator
public class MultivariateGaussianEstimator extends Object implements MultivariateEstimator, Serializable
Implementation of maximum likelihood Multivariate Distribution Estimation using Normal Distribution.
Version:
$Revision: 12898 $
Author:
Uday Kamath, PhD, George Mason University, Eibe Frank, University of Waikato
See Also:

  • Field Summary

    Fields
    Modifier and Type
    Field
    Description
    static final double
    Log2PI
    Log of twice the number pi: log(2*pi).

  • Constructor Summary

    Constructors
    Constructor
    Description
    MultivariateGaussianEstimator()
     

  • Method Summary

    Modifier and Type
    Method
    Description
    void
    estimate(double[][] observations, double[] weights)
    Generates the estimator based on the given observations and weight vector.
    double[][]
    estimatePooled(double[][][] observations, double[][] weights)
    Generates pooled estimator for linear discriminant analysis based on the given groups of observations and weight vectors.
    double[]
    getMean()
    Returns the mean vector.
    double
    getRidge()
    Get the value of Ridge.
    double
    logDensity(double[] valuePassed)
    Returns the log of the density value for the given vector.
    static void
    main(String[] args)
    Main method for testing this class.
    String
    ridgeTipText()
    Returns the tip text for this property
    void
    setRidge(double newRidge)
    Set the value of Ridge.
    String
    toString()
    Returns string summarizing the estimator.

    Methods inherited from class java.lang.Object

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

  • Field Details

    • Log2PI

      public static final double Log2PI
      Log of twice the number pi: log(2*pi).

  • Constructor Details

    • MultivariateGaussianEstimator

      public MultivariateGaussianEstimator()

  • Method Details

    • toString

      public String toString()
      Returns string summarizing the estimator.
      Overrides:
      toString in class Object

    • getMean

      public double[] getMean()
      Returns the mean vector.

    • logDensity

      public double logDensity(double[] valuePassed)
      Returns the log of the density value for the given vector.
      Specified by:
      logDensity in interface MultivariateEstimator
      Parameters:
      valuePassed - input vector
      Returns:
      log density based on given distribution

    • estimate

      public void estimate(double[][] observations, double[] weights)
      Generates the estimator based on the given observations and weight vector. Equal weights are assumed if the weight vector is null.
      Specified by:
      estimate in interface MultivariateEstimator
      Parameters:
      observations - the value to add
      weights - the weight of the value

    • estimatePooled

      public double[][] estimatePooled(double[][][] observations, double[][] weights)
      Generates pooled estimator for linear discriminant analysis based on the given groups of observations and weight vectors. The pooled covariance matrix is the weighted mean of the per-group covariance matrices. The pooled mean vector is the mean vector for all observations.
      Returns:
      the per group mean vectors

    • ridgeTipText

      public String ridgeTipText()
      Returns the tip text for this property
      Returns:
      tip text for this property suitable for displaying in the explorer/experimenter gui

    • getRidge

      public double getRidge()
      Get the value of Ridge.
      Returns:
      Value of Ridge.

    • setRidge

      public void setRidge(double newRidge)
      Set the value of Ridge.
      Parameters:
      newRidge - Value to assign to Ridge.

    • main

      public static void main(String[] args)
      Main method for testing this class.
      Parameters:
      args - command-line parameters