diva.sketch.classification

Class BayesClassifier

java.lang.Object

diva.sketch.classification.AbstractClassifier

diva.sketch.classification.BayesClassifier

All Implemented Interfaces:

Classifier, TrainableClassifier

public class BayesClassifier
extends AbstractClassifier

A naive bayes classifier. The training process calculates mu and sigma for each feature (a random variable) of a class, and the classification process uses the joint p.d.f. to compute the probability of an example belonging to a particular class.

Version:

$Revision: 1.3 $

Author:

Heloise Hse (hwawen@eecs.berkeley.edu), Michael Shilman (michaels@eecs.berkeley.edu)

Field Summary

Fields

Modifier and Type	Field and Description
protected static double	MIN_SIGMA The minimum sigma value; used to avoid divide-by-zero errors.

Fields inherited from class diva.sketch.classification.AbstractClassifier

_weights

Constructor Summary

Constructors

Constructor and Description
BayesClassifier()

Method Summary

Modifier and Type	Method and Description
Classification	classify(FeatureSet fs) Given a feature vector (fs), compute the joint probability of each class.
void	train(TrainingSet tset) Compute mu's and sigma's for each class, also computes the coefficients (one per class) that are used in the joint p.d.f.

Methods inherited from class diva.sketch.classification.AbstractClassifier

clear, debug, isIncremental

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

MIN_SIGMA

protected static final double MIN_SIGMA

The minimum sigma value; used to avoid divide-by-zero errors.

See Also:

Constant Field Values

Constructor Detail

BayesClassifier

public BayesClassifier()

Method Detail

train

public void train(TrainingSet tset)
           throws ClassifierException

Compute mu's and sigma's for each class, also computes the coefficients (one per class) that are used in the joint p.d.f. calculation.

Specified by:

train in interface TrainableClassifier

Overrides:

train in class AbstractClassifier

Throws:

ClassifierException

classify

public Classification classify(FeatureSet fs)
                        throws ClassifierException

Given a feature vector (fs), compute the joint probability of each class. p(x)=(1/product(sigma_i)*(2*PI)^n/2)*exp(-0.5*sum((x_i-mu_i)/sigma_i)^2) i = 1,2,...n n = number of features

Throws:

ClassifierException