Prior (original) (raw)

• java.lang.Object

• • weka.classifiers.bayes.blr.Prior

• All Implemented Interfaces:
  java.io.Serializable, RevisionHandler
  Direct Known Subclasses:
  GaussianPriorImpl, LaplacePriorImpl

public abstract class Prior
extends java.lang.Object
implements java.io.Serializable, RevisionHandler
This is an interface to plug various priors into the Bayesian Logistic Regression Model.
Version: Revision:1.2Revision: 1.2 Revision:1.2
Author:
Navendu Garg (gargnav@iit.edu)
See Also:
Serialized Form

• • Constructor Summary

  Constructors

  Constructor and Description
  Prior()

  • Method Summary

  All Methods Instance Methods Concrete Methods

  Modifier and Type	Method and Description
  void	computelogLikelihood(double[] betas,Instances instances) Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}
  void	computePenalty(double[] betas, double[] hyperparameters) Skeleton function to compute penalty terms.
  double	getLoglikelihood()
  double	getLogPosterior()
  double	getPenalty()
  double	update(int j,Instances instances, double beta, double hyperparameter, double[] r, double deltaV) Interface for the update functions for different types of priors.

     * ### Methods inherited from class java.lang.Object  
     `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`  
     * ### Methods inherited from interface weka.core.[RevisionHandler](../../../../weka/core/RevisionHandler.html "interface in weka.core")  
     `[getRevision](../../../../weka/core/RevisionHandler.html#getRevision--)`

• • Constructor Detail

     * #### Prior  
     public Prior()  

  • Method Detail

    * #### update  
    public double update(int j,  
                         [Instances](../../../../weka/core/Instances.html "class in weka.core") 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](../../../../weka/core/Instances.html "class in weka.core") 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.