Uses of Class cc.mallet.classify.Classifier (Mallet 2 API)

Packages that use Classifier
Package	Description
cc.mallet.classify	Classes for training and classifying instances.
cc.mallet.classify.evaluate	Classes for computing and displaying the quaility of a classification trial, including accuracy, precision, and confusion matrix.
cc.mallet.cluster.neighbor_evaluator
cc.mallet.pipe	Classes for processing arbitrary data into instances.
cc.mallet.share.upenn	Utilities that currently include a command line wrapper for the maxent classifier.

Uses of Classifier in cc.mallet.classify

Classes in cc.mallet.classify with type parameters of type Classifier
Modifier and Type	Class	Description
`class`	`ClassifierTrainer<C extends Classifier>`	Each ClassifierTrainer trains one Classifier based on various interfaces for consuming training data.
`static interface`	`ClassifierTrainer.ByActiveLearning<C extends Classifier>`	For active learning, in which this trainer will select certain instances and request that the Labeler instance label them.
`static interface`	`ClassifierTrainer.ByIncrements<C extends Classifier>`	For various kinds of online learning by batches, where training instances are presented, consumed for learning immediately.
`static interface`	`ClassifierTrainer.ByInstanceIncrements<C extends Classifier>`	For online learning that can operate on one instance at a time.
`static interface`	`ClassifierTrainer.ByOptimization<C extends Classifier>`
`static class`	`ClassifierTrainer.Factory<CT extends ClassifierTrainer<? extends Classifier>>`	Instances of a Factory know how to create new ClassifierTrainers to apply to new Classifiers.

Subclasses of Classifier in cc.mallet.classify
Modifier and Type	Class	Description
`class`	`AdaBoost`	AdaBoost Robert E.
`class`	`AdaBoostM2`	AdaBoostM2
`class`	`BaggingClassifier`
`class`	`BalancedWinnow`	Classification methods of BalancedWinnow algorithm.
`class`	`C45`	A C4.5 Decision Tree classifier.
`class`	`ClassifierEnsemble`	Classifer for an ensemble of classifers, combined with learned weights.
`class`	`ConfidencePredictingClassifier`
`class`	`DecisionTree`	Decision Tree classifier.
`class`	`MaxEnt`	Maximum Entropy (AKA Multivariate Logistic Regression) classifier.
`class`	`MCMaxEnt`	Maximum Entropy classifier.
`class`	`MostFrequentClassifier`	A Classifier that will return the most frequent class label based on a training set.
`class`	`NaiveBayes`	A classifier that classifies instances according to the NaiveBayes method.
`class`	`PRAuxClassifier`	Auxiliary model (q) for E-step/I-projection in PR training.
`class`	`RandomClassifier`	A Classifier that will return a randomly selected class label.
`class`	`RankMaxEnt`	Rank Maximum Entropy classifier.
`class`	`Winnow`	Classification methods of Winnow2 algorithm.

Methods in cc.mallet.classify that return Classifier
Modifier and Type	Method	Description
`Classifier`	Classification.`getClassifier()`
`Classifier`	FeatureSelectingClassifierTrainer.`getClassifier()`
`Classifier`	Trial.`getClassifier()`
`Classifier`	FeatureSelectingClassifierTrainer.`train(InstanceList trainingSet)`

Methods in cc.mallet.classify with parameters of type Classifier
Modifier and Type	Method	Description
`abstract CT`	ClassifierTrainer.Factory.`newClassifierTrainer(Classifier initialClassifier)`
`DecisionTreeTrainer`	DecisionTreeTrainer.Factory.`newClassifierTrainer(Classifier initialClassifier)`
`NaiveBayesTrainer`	NaiveBayesTrainer.Factory.`newClassifierTrainer(Classifier initialClassifier)`

Constructors in cc.mallet.classify with parameters of type Classifier
Constructor	Description
`AdaBoost(Pipe instancePipe, Classifier[] weakClassifiers, double[] alphas)`
`AdaBoostM2(Pipe instancePipe, Classifier[] weakClassifiers, double[] alphas)`
`BaggingClassifier(Pipe instancePipe, Classifier[] baggedClassifiers)`
`Classification(Instance instance, Classifier classifier, Labeling labeling)`
`ClassifierEnsemble(Classifier[] classifiers, double[] weights)`
`ClassifierEnsembleTrainer(Classifier[] classifiers)`
`ConfidencePredictingClassifier(Classifier underlyingClassifier, Classifier confidencePredictingClassifier)`
`Trial(Classifier c, InstanceList ilist)`

Uses of Classifier in cc.mallet.classify.evaluate

Constructors in cc.mallet.classify.evaluate with parameters of type Classifier
Constructor	Description
`AccuracyCoverage(Classifier C, InstanceList ilist, int numBuckets, java.lang.String title)`
`AccuracyCoverage(Classifier C, InstanceList ilist, java.lang.String title)`

Uses of Classifier in cc.mallet.cluster.neighbor_evaluator

Methods in cc.mallet.cluster.neighbor_evaluator that return Classifier
Modifier and Type	Method	Description
`Classifier`	ClassifyingNeighborEvaluator.`getClassifier()`

Constructors in cc.mallet.cluster.neighbor_evaluator with parameters of type Classifier
Constructor	Description
`ClassifyingNeighborEvaluator(Classifier classifier, java.lang.String scoringLabel)`
`MedoidEvaluator(Classifier classifier, java.lang.String scoringLabel)`
`MedoidEvaluator(Classifier classifier, java.lang.String scoringLabel, boolean singleLink, boolean mergeFirst)`
`PairwiseEvaluator(Classifier classifier, java.lang.String scoringLabel, PairwiseEvaluator.CombiningStrategy combiningStrategy, boolean mergeFirst)`
`RankingNeighborEvaluator(Classifier classifier)`

Uses of Classifier in cc.mallet.pipe

Subclasses of Classifier in cc.mallet.pipe
Modifier and Type	Class	Description
`static class`	`AddClassifierTokenPredictions.TokenClassifiers`	This inner class represents the trained token classifiers.

Uses of Classifier in cc.mallet.share.upenn

Methods in cc.mallet.share.upenn that return Classifier
Modifier and Type	Method	Description
`static Classifier`	MaxEntShell.`load(java.io.File modelFile)`	Load a classifier from a file.
`static Classifier`	MaxEntShell.`train(java.lang.String[][] features, java.lang.String[] labels, double var, java.io.File save)`	Train a maxent classifier.
`static Classifier`	MaxEntShell.`train(java.util.Iterator<Instance> data, double var, java.io.File save)`	Train a maxent classifier.

Methods in cc.mallet.share.upenn with parameters of type Classifier
Modifier and Type	Method	Description
`static Classification`	MaxEntShell.`classify(Classifier classifier, java.lang.String[] features)`	Compute the maxent classification of an instance.
`static Classification[]`	MaxEntShell.`classify(Classifier classifier, java.lang.String[][] features)`	Compute the maxent classifications of an array of instances
`static Classification[]`	MaxEntShell.`classify(Classifier classifier, java.util.Iterator<Instance> data)`	Compute the maxent classifications for unlabeled instances given by an iterator.
`static double`	MaxEntShell.`test(Classifier classifier, java.lang.String[][] features, java.lang.String[] labels)`	Test a maxent classifier.
`static double`	MaxEntShell.`test(Classifier classifier, java.util.Iterator<Instance> data)`	Test a maxent classifier.