Package edu.umass.cs.mallet.base.classify

Classes for training and classifying instances.

See:
          Description

Interface Summary
Boostable This interface is a tag indicating that the classifier attends to the InstanceList.getInstanceWeight() weights when training.
ClassifierEvaluating  
 

Class Summary
AbstractClassifierEvaluating Created: Apr 13, 2005
AccuracyEvaluator  
AdaBoost AdaBoost Robert E.
AdaBoostM2 AdaBoostM2
AdaBoostM2Trainer This version of AdaBoost can handle multi-class problems.
AdaBoostTrainer This version of AdaBoost should be used only for binary classification.
BaggingClassifier  
BaggingTrainer Bagging Trainer.
BalancedWinnow Classification methods of BalancedWinnow algorithm.
BalancedWinnowTrainer An implementation of the training methods of a BalancedWinnow on-line classifier.
C45 A C4.5 Decision Tree classifier.
C45.Node  
C45Trainer A C4.5 decision tree learner, approximtely.
Classification The result of classifying a single instance.
Classifier Abstract parent of all Classifiers.
ClassifierTrainer Abstract parent of all classifier trainers.
ConfidencePredictingClassifier  
ConfidencePredictingClassifierTrainer  
DecisionTree Decision Tree classifier.
DecisionTree.Node  
DecisionTreeTrainer A decision tree learner, roughly ID3.
FeatureSelectingClassifierTrainer Adaptor for adding feature selection to a classifier trainer.
IncrementalClassifierTrainer Adds the notion of incremental training to a ClassifierTrainer, through the availability of incrementalTrain() methods, which parallel the train() methods.
MaxEnt Maximum Entropy classifier.
MaxEntTrainer The trainer for a Maximum Entropy classifier.
MCMaxEnt Maximum Entropy classifier.
MCMaxEntTrainer The trainer for a Maximum Entropy classifier.
NaiveBayes A classifier that classifies instances according to the NaiveBayes method.
NaiveBayesTrainer Class used to generate a NaiveBayes classifier from a set of training data.
Trial A convenience class for running an instance list through a classifier and storing the instancelist, the classifier, and the resulting classifications of each instance.
TUI Text User Interface for classification (unsupported).
Winnow Classification methods of Winnow2 algorithm.
WinnowTrainer An implementation of the training methods of a Winnow2 on-line classifier.
 

Package edu.umass.cs.mallet.base.classify Description

Classes for training and classifying instances. All classification techniques in MALLET are implemented 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.