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	PRAuxClassifier Auxiliary model (q) for E-step/I-projection in PR training.
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	FeatureSelectingClassifierTrainer.getClassifier()
Classifier	Classification.getClassifier()
Classifier	FeatureSelectingClassifierTrainer.train(InstanceList trainingSet)

Methods in cc.mallet.classify with parameters of type Classifier

NaiveBayesTrainer	NaiveBayesTrainer.Factory.newClassifierTrainer(Classifier initialClassifier)
DecisionTreeTrainer	DecisionTreeTrainer.Factory.newClassifierTrainer(Classifier initialClassifier)
abstract CT	ClassifierTrainer.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.