edu.umass.cs.mallet.base.classify

Class ClassifierTrainer

java.lang.Object

edu.umass.cs.mallet.base.classify.ClassifierTrainer

Direct Known Subclasses:

AdaBoostM2Trainer, AdaBoostTrainer, BaggingTrainer, BalancedWinnowTrainer, C45Trainer, ConfidencePredictingClassifierTrainer, DecisionTreeTrainer, FeatureSelectingClassifierTrainer, IncrementalClassifierTrainer, MaxEntTrainer, MCMaxEntTrainer, WinnowTrainer

public abstract class ClassifierTrainer
extends Object

Abstract parent of all classifier trainers.

All classification techniques in MALLET are implement as two classes: a trainer and a classifier. The trainer injests the training data and creates a classifier that holds the parameters set during training. The classifier applies those parameters to an Instance to produce a classification of the Instance.

A concrete trainer is required only to be able to train from an InstanceList. Trainers that can incrementally train are subclasses of IncrementalTrainingClassifier.

There are some rudimentary command line facilities here. The preferred command line interface tools for document classification are: Csv2Vectors, Text2Vectors, Vectors2Classify, Vectors2Info, and Vectors2Vectors

Author:

Andrew McCallum mccallum@cs.umass.edu

See Also:

Classifier

Constructor Summary

Constructors

Constructor and Description
ClassifierTrainer()

Method Summary

Modifier and Type	Method and Description
static void	main(String[] args)
String	toString()
Classifier	train(InstanceList trainingSet)
Classifier	train(InstanceList trainingSet, InstanceList validationSet)
Classifier	train(InstanceList trainingSet, InstanceList validationSet, InstanceList testSet)
Classifier	train(InstanceList trainingSet, InstanceList validationSet, InstanceList testSet, ClassifierEvaluating evaluator)
abstract Classifier	train(InstanceList trainingSet, InstanceList validationSet, InstanceList testSet, ClassifierEvaluating evaluator, Classifier initialClassifier) Return a new classifier tuned using the three arguments.

Methods inherited from class java.lang.Object

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

Constructor Detail

ClassifierTrainer

public ClassifierTrainer()

Method Detail

train

public Classifier train(InstanceList trainingSet)

train

public Classifier train(InstanceList trainingSet,
                        InstanceList validationSet)

train

public Classifier train(InstanceList trainingSet,
                        InstanceList validationSet,
                        InstanceList testSet)

train

public Classifier train(InstanceList trainingSet,
                        InstanceList validationSet,
                        InstanceList testSet,
                        ClassifierEvaluating evaluator)

train

public abstract Classifier train(InstanceList trainingSet,
                                 InstanceList validationSet,
                                 InstanceList testSet,
                                 ClassifierEvaluating evaluator,
                                 Classifier initialClassifier)

Return a new classifier tuned using the three arguments.

Parameters:

trainingSet - examples used to set parameters.

validationSet - examples used to tune meta-parameters. May be null.

testSet - examples not examined at all for training, but passed on to diagnostic routines. May be null.

initialClassifier - training process may start from here. The parameters of the initialClassifier are not modified. May be null.

toString

public String toString()

Overrides:

toString in class Object

main

public static void main(String[] args)
                 throws bsh.EvalError,
                        IOException

Throws:

bsh.EvalError

IOException