Package com.aliasi.classify

Classes for classifying data and evaluation.

See: Description

Interface Summary

Interface	Description
BaseClassifier<E>	The BaseClassifier interface specifies a single method for first-best classification.
ConditionalClassifier<E>	The ConditionalClassifier interface specifies a single method for n-best classification with conditional category probabilities.
JointClassifier<E>	The JointClassifier interface specifies a single method for n-best classification with joint input and category probabilities.
RankedClassifier<E>	The RankedClassifier interface specifies a single classification method that returns n-best classifications of inputs.
ScoredClassifier<E>	The ScoredClassifier interface specifies a single method for n-best scored classification.

Class Summary

Class	Description
BaseClassifierEvaluator<E>	A BaseClassifierEvaluator provides an evaluation harness for first-best classifiers.
BernoulliClassifier<E>	A BernoulliClassifier provides a feature-based classifier where feature values are reduced to booleans based on a specified threshold.
BigVectorClassifier	A BigVectorClassifier provides an efficient linear classifier implementation for large numbers of categories.
BinaryLMClassifier	A BinaryLMClassifier is a boolean dynamic language model classifier for use when there are two categories, but training data is only available for one of the categories.
Classification	A Classification provides a first-best category.
Classified<E>	A Classified represents an object that has been classified with a first-best classification.
ConditionalClassification	A ConditionalClassification is a scored classification which estimates conditional probabilities of categories given an input.
ConditionalClassifierEvaluator<E>	A ConditionalClassifierEvaluator provides an evaluation harness for conditional probability-based n-best classifiers.
ConfusionMatrix	An instance of ConfusionMatrix represents a quantitative comparison between two classifiers over a fixed set of categories on a number of test cases.
DynamicLMClassifier<L extends LanguageModel.Dynamic>	A DynamicLMClassifier is a language model classifier that accepts training events of categorized character sequences.
JointClassification	A JointClassification is a conditional classification derived from a joint probability assignment to each category and the object being classified.
JointClassifierEvaluator<E>	A JointClassifierEvaluator provides an evaluation harness for joint probability-based n-best classifiers.
KnnClassifier<E>	A KnnClassifier implements k-nearest-neighor classification based on feature extraction and a vector proximity or distance.
LMClassifier<L extends LanguageModel,M extends MultivariateDistribution>	An LMClassifier performs joint probability-based classification of character sequences into non-overlapping categories based on language models for each category and a multivariate distribution over categories.
LogisticRegressionClassifier<E>	A LogisticRegressionClassifier provides conditional probability classifications of input objects using an underlying logistic regression model and feature extractor.
NaiveBayesClassifier	A NaiveBayesClassifier provides a trainable naive Bayes text classifier, with tokens as features.
PerceptronClassifier<E>	A PerceptronClassifier implements a binary classifier based on an averaged kernel-based perceptron.
PrecisionRecallEvaluation	A PrecisionRecallEvaluation collects and reports a suite of descriptive statistics for binary classification tasks.
RankedClassification	A RankedClassification provides a classification with an ordered n-best list of category results.
RankedClassified<E>	A RankedClassified represents an object that has been classified with a ranked classification.
RankedClassifierEvaluator<E>	A RankedClassifierEvaluator provides an evaluation harness for ranked classifiers.
ScoredClassification	A ScoredClassification is a ranked classification where each category also has a score that determines the ranking.
ScoredClassifierEvaluator<E>	A ScoredClassifierEvaluator provides an evaluation harness for score-based classifiers.
ScoredPrecisionRecallEvaluation	A ScoredPrecisionRecallEvaluation provides an evaluation based on the precision-recall operating points and sensitivity-specificity operating points.
TfIdfClassifierTrainer<E>	A TfIdfClassifierTrainer provides a framework for training discriminative classifiers based on term-frequency (TF) and inverse document frequency (IDF) weighting of features.
TradNaiveBayesClassifier	A TradNaiveBayesClassifier implements a traditional token-based approach to naive Bayes text classification.

Package com.aliasi.classify Description

Classes for classifying data and evaluation. Throughout, we use the term "category" rather than "class" or "type", to avoid confusion with the object-oriented notion of class in Java.