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## Uses of Class
cc.mallet.classify.Classifier

Packages that use Classifier
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
`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
`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` | `NaiveBayes` A classifier that classifies instances according to the NaiveBayes method.
`class` | `RankMaxEnt` Rank Maximum Entropy classifier.
`class` | `Winnow` Classification methods of Winnow2 algorithm.

Methods in cc.mallet.classify that return Classifier
`Classifier` | `Trial.getClassifier()`
`Classifier` | `Classification.getClassifier()`
`Classifier` | `FeatureSelectingClassifierTrainer.getClassifier()`
`Classifier` | `FeatureSelectingClassifierTrainer.train(InstanceList trainingSet)`

Methods in cc.mallet.classify with parameters of type Classifier
`abstract CT` | `ClassifierTrainer.Factory.newClassifierTrainer(Classifier initialClassifier)`
`NaiveBayesTrainer` | `NaiveBayesTrainer.Factory.newClassifierTrainer(Classifier initialClassifier)`
`DecisionTreeTrainer` | `DecisionTreeTrainer.Factory.newClassifierTrainer(Classifier initialClassifier)`

Constructors in cc.mallet.classify with parameters of type Classifier
`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
`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
`Classifier` | `ClassifyingNeighborEvaluator.getClassifier()`

Constructors in cc.mallet.cluster.neighbor_evaluator with parameters of type Classifier
`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
`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
`static Classifier` | `MaxEntShell.load(java.io.File modelFile)` Load a classifier from a file.
`static Classifier` | `MaxEntShell.train(java.util.Iterator<Instance> data, double var, java.io.File save)` Train a maxent classifier.
`static Classifier` | `MaxEntShell.train(java.lang.String[][] features, java.lang.String[] labels, double var, java.io.File save)` Train a maxent classifier.

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

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