Package weka.classifiers.bayes.blr

Class Prior

java.lang.Object
weka.classifiers.bayes.blr.Prior
All Implemented Interfaces:
Serializable, RevisionHandler
Direct Known Subclasses:
GaussianPriorImpl, LaplacePriorImpl
public abstract class Prior extends Object implements Serializable, RevisionHandler
This is an interface to plug various priors into the Bayesian Logistic Regression Model.
Version:
$Revision: 1.2 $
Author:
Navendu Garg (gargnav@iit.edu)
See Also:

  • Constructor Details

    • Prior

      public Prior()

  • Method Details

    • update

      public double update(int j, Instances instances, double beta, double hyperparameter, double[] r, double deltaV)
      Interface for the update functions for different types of priors.

    • computelogLikelihood

      public void computelogLikelihood(double[] betas, Instances instances)
      Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}
      Parameters:
      betas -
      instances -

    • computePenalty

      public void computePenalty(double[] betas, double[] hyperparameters)
      Skeleton function to compute penalty terms.
      Parameters:
      betas -
      hyperparameters -

    • getLoglikelihood

      public double getLoglikelihood()
      Returns:
      log-likelihood value.

    • getLogPosterior

      public double getLogPosterior()
      Returns:
      regularized log posterior value.

    • getPenalty

      public double getPenalty()
      Returns:
      penalty term.