Uses of Class
com.aliasi.classify.Classified

Packages that use Classified

Package	Description
com.aliasi.classify	Classes for classifying data and evaluation.
com.aliasi.features	Classes for extracting feature vectors from objects and parsing objects for feature handlers.

Uses of Classified in com.aliasi.classify

Subclasses of Classified in com.aliasi.classify

Modifier and Type	Class and Description
class	RankedClassified<E> A RankedClassified represents an object that has been classified with a ranked classification.

Methods in com.aliasi.classify that return types with arguments of type Classified

Modifier and Type	Method and Description
List<Classified<E>>	BaseClassifierEvaluator.falseNegatives(String category) Returns the list of false negative cases along with their classifications for items of the specified category.
List<Classified<E>>	BaseClassifierEvaluator.falsePositives(String category) Returns the list of false positive cases along with their classifications for items of the specified category.
List<Classified<E>>	BaseClassifierEvaluator.trueNegatives(String category) Returns the list of true negative cases along with their classifications for items of the specified category.
List<Classified<E>>	BaseClassifierEvaluator.truePositives(String category) Returns the list of true positive cases along with their classifications for items of the specified category.

Methods in com.aliasi.classify with parameters of type Classified

Modifier and Type	Method and Description
void	BinaryLMClassifier.handle(Classified<CharSequence> classified) Train this classifier using the character sequence from the specified classified object if the best category of the classification is the accept category for this binary classifier.
void	TradNaiveBayesClassifier.handle(Classified<CharSequence> classifiedObject) Trains the classifier with the specified classified character sequence.
void	DynamicLMClassifier.handle(Classified<CharSequence> classified) Provides a training instance for the specified character sequence using the best category from the specified classification.
void	BernoulliClassifier.handle(Classified<E> classified) Handle the specified training classified object.
void	TfIdfClassifierTrainer.handle(Classified<E> classified) Handle the specified classified object as training data.
void	KnnClassifier.handle(Classified<E> classifiedObject) Handle the specified classified object as a training instance.
void	RankedClassifierEvaluator.handle(Classified<E> classified)
void	ScoredClassifierEvaluator.handle(Classified<E> classified)
void	BaseClassifierEvaluator.handle(Classified<E> classified) Add the specified classified object to this evaluator.
void	ConditionalClassifierEvaluator.handle(Classified<E> classified)

Method parameters in com.aliasi.classify with type arguments of type Classified

Modifier and Type	Method and Description
static Iterator<TradNaiveBayesClassifier>	TradNaiveBayesClassifier.emIterator(TradNaiveBayesClassifier initialClassifier, Factory<TradNaiveBayesClassifier> classifierFactory, Corpus<ObjectHandler<Classified<CharSequence>>> labeledData, Corpus<ObjectHandler<CharSequence>> unlabeledData, double minTokenCount) Apply the expectation maximization (EM) algorithm to train a traditional naive Bayes classifier using the specified labeled and unabled data, initial classifier and factory for creating subsequent factories.
static TradNaiveBayesClassifier	TradNaiveBayesClassifier.emTrain(TradNaiveBayesClassifier initialClassifier, Factory<TradNaiveBayesClassifier> classifierFactory, Corpus<ObjectHandler<Classified<CharSequence>>> labeledData, Corpus<ObjectHandler<CharSequence>> unlabeledData, double minTokenCount, int maxEpochs, double minImprovement, Reporter reporter) Apply the expectation maximization (EM) algorithm to train a traditional naive Bayes classifier using the specified labeled and unabled data, initial classifier and factory for creating subsequent factories, maximum number of epochs, minimum improvement per epoch, and reporter to which progress reports are sent.
static <F> LogisticRegressionClassifier<F>	LogisticRegressionClassifier.train(Corpus<ObjectHandler<Classified<F>>> corpus, FeatureExtractor<? super F> featureExtractor, int minFeatureCount, boolean addInterceptFeature, RegressionPrior prior, AnnealingSchedule annealingSchedule, double minImprovement, int minEpochs, int maxEpochs, Reporter reporter) Returns a trained logistic regression classifier given the specified feature extractor, training corpus, model priors and search parameters.
static <F> LogisticRegressionClassifier<F>	LogisticRegressionClassifier.train(Corpus<ObjectHandler<Classified<F>>> corpus, FeatureExtractor<? super F> featureExtractor, int minFeatureCount, boolean addInterceptFeature, RegressionPrior prior, int blockSize, LogisticRegressionClassifier<F> hotStart, AnnealingSchedule annealingSchedule, double minImprovement, int rollingAverageSize, int minEpochs, int maxEpochs, ObjectHandler<LogisticRegressionClassifier<F>> classifierHandler, Reporter reporter) Returns a trained logistic regression classifier given the specified feature extractor, training corpus, model priors and search parameters.

Constructor parameters in com.aliasi.classify with type arguments of type Classified

Constructor and Description

PerceptronClassifier(Corpus<ObjectHandler<Classified<E>>> corpus, FeatureExtractor<? super E> featureExtractor, KernelFunction kernelFunction, String corpusAcceptCategory, int numIterations, String outputAcceptCategory, String outputRejectCategory) Construct a perceptron classifier from the specified feature extractor, corpus with designated accept category, polynomial kernel degree and number of training iterations, and output accept and reject categories.

Uses of Classified in com.aliasi.features

Constructor parameters in com.aliasi.features with type arguments of type Classified

Constructor and Description
ZScoreFeatureExtractor(Corpus<ObjectHandler<Classified<E>>> corpus, FeatureExtractor<? super E> extractor) Construct a z-core feature extractor from the specified base feature extractor and the training section of the supplied corpus.