Package cc.mallet.classify

Class WinnowTrainer

java.lang.Object

cc.mallet.classify.ClassifierTrainer<Winnow>

cc.mallet.classify.WinnowTrainer

public class WinnowTrainer
extends ClassifierTrainer<Winnow>

An implementation of the training methods of a Winnow2 on-line classifier. Given an instance xi, the algorithm computes Sum(xi*wi), where wi is the weight for that feature in the given class. If the Sum is greater than some threshold theta, then the classifier guess true for that class. Only when the classifier makes a mistake are the weights updated in one of two steps: Promote: guessed 0 and answer was 1. Multiply all weights of present features by alpha. Demote: guessed 1 and answer was 0. Divide all weights of present features by beta. Limitations: Winnow2 only considers binary feature vectors (i.e. whether or not the feature is present, not its value).

Nested Class Summary

Nested classes/interfaces inherited from class cc.mallet.classify.ClassifierTrainer

ClassifierTrainer.ByActiveLearning<C extends Classifier>, ClassifierTrainer.ByIncrements<C extends Classifier>, ClassifierTrainer.ByInstanceIncrements<C extends Classifier>, ClassifierTrainer.ByOptimization<C extends Classifier>, ClassifierTrainer.Factory<CT extends ClassifierTrainer<? extends Classifier>>

Field Summary

Fields inherited from class cc.mallet.classify.ClassifierTrainer

finishedTraining, validationSet

Constructor Summary

Constructors

Constructor	Description
WinnowTrainer()	Default constructor.
WinnowTrainer(double a, double b)	Sets alpha and beta and default value for theta
WinnowTrainer(double a, double b, double nfact)	Sets alpha, beta, and nfactor

Method Summary

Modifier and Type	Method	Description
Winnow	getClassifier()
Winnow	train(InstanceList trainingList)	Trains winnow on the instance list, updating weights according to errors

Methods inherited from class cc.mallet.classify.ClassifierTrainer

getValidationInstances, isFinishedTraining, setValidationInstances

Methods inherited from class java.lang.Object

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

Constructor Detail

WinnowTrainer

public WinnowTrainer()

Default constructor. Sets all features to defaults.

WinnowTrainer

public WinnowTrainer(double a,
                     double b)

Sets alpha and beta and default value for theta

Parameters:

a - alpha value

b - beta value

WinnowTrainer

public WinnowTrainer(double a,
                     double b,
                     double nfact)

Sets alpha, beta, and nfactor

Parameters:

a - alpha value

b - beta value

nfact - nfactor value

Method Detail

getClassifier

public Winnow getClassifier()

Specified by:

getClassifier in class ClassifierTrainer<Winnow>

train

public Winnow train(InstanceList trainingList)

Trains winnow on the instance list, updating weights according to errors

Specified by:

train in class ClassifierTrainer<Winnow>

Parameters:

ilist - Instance list to be trained on

Returns:

Classifier object containing learned weights