Uses of Interface
de.jungblut.classification.Classifier
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Uses of Classifier in de.jungblut.classification
Classes in de.jungblut.classification with type parameters of type Classifier Modifier and Type Interface Description interfaceClassifierFactory<A extends Classifier>Factory interface for building new classifiers, majorly used in crossvalidation to generate new classifiers when needed.Classes in de.jungblut.classification that implement Classifier Modifier and Type Class Description classAbstractClassifierAbstract base class for classifiers.classUntrainableClassifierMethods in de.jungblut.classification that return Classifier Modifier and Type Method Description default ClassifierPredictor. asClassifier()Backward compatibility method to make online-ml project's predictors work with almost everything in this library. -
Uses of Classifier in de.jungblut.classification.bayes
Classes in de.jungblut.classification.bayes that implement Classifier Modifier and Type Class Description classMultinomialNaiveBayesMultinomial naive bayes classifier. -
Uses of Classifier in de.jungblut.classification.eval
Classes in de.jungblut.classification.eval with type parameters of type Classifier Modifier and Type Class Description classEvaluationListener<A extends Classifier>The evaluation listener is majorly used to track the overfitting of a classifier while training.classTestSetIterationCallback<T extends Classifier>This callback is used to evaluate the performance on a held-out test set.interfaceWeightMapper<A extends Classifier>This interface helps to map minimizable weights of aCostFunctionto aClassifierimplementation.Methods in de.jungblut.classification.eval with type parameters of type Classifier Modifier and Type Method Description static <A extends Classifier>
Evaluator.EvaluationResultEvaluator. crossValidateClassifier(ClassifierFactory<A> classifierFactory, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, int numLabels, int folds, java.lang.Double threshold, boolean verbose)Does a k-fold crossvalidation on the given classifiers with features and outcomes.static <A extends Classifier>
Evaluator.EvaluationResultEvaluator. crossValidateClassifier(ClassifierFactory<A> classifierFactory, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, int numLabels, int folds, java.lang.Double threshold, int numThreads, boolean verbose)Does a k-fold crossvalidation on the given classifiers with features and outcomes.static <A extends Classifier>
Evaluator.EvaluationResultEvaluator. tenFoldCrossValidation(ClassifierFactory<A> classifierFactory, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, int numLabels, java.lang.Double threshold, boolean verbose)Does a 10 fold crossvalidation.static <A extends Classifier>
Evaluator.EvaluationResultEvaluator. tenFoldCrossValidation(ClassifierFactory<A> classifierFactory, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, int numLabels, java.lang.Double threshold, int numThreads, boolean verbose)Does a 10 fold crossvalidation.Methods in de.jungblut.classification.eval with parameters of type Classifier Modifier and Type Method Description static Evaluator.EvaluationResultEvaluator. evaluateClassifier(Classifier classifier, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, float splitFraction, boolean random)Trains and evaluates the given classifier with a test split.static Evaluator.EvaluationResultEvaluator. evaluateClassifier(Classifier classifier, de.jungblut.math.DoubleVector[] features, de.jungblut.math.DoubleVector[] outcome, float splitFraction, boolean random, java.lang.Double threshold)Trains and evaluates the given classifier with a test split.static Evaluator.EvaluationResultEvaluator. evaluateSplit(Classifier classifier, EvaluationSplit split)Evaluates a given train/test split with the given classifier.static Evaluator.EvaluationResultEvaluator. evaluateSplit(Classifier classifier, EvaluationSplit split, java.lang.Double threshold)Evaluates a given train/test split with the given classifier.static Evaluator.EvaluationResultEvaluator. evaluateSplit(Classifier classifier, de.jungblut.math.DoubleVector[] trainFeatures, de.jungblut.math.DoubleVector[] trainOutcome, de.jungblut.math.DoubleVector[] testFeatures, de.jungblut.math.DoubleVector[] testOutcome, java.lang.Double threshold)Evaluates a given train/test split with the given classifier. -
Uses of Classifier in de.jungblut.classification.knn
Classes in de.jungblut.classification.knn that implement Classifier Modifier and Type Class Description classAbstractKNearestNeighboursK nearest neighbour classification algorithm that is seeded with a "database" of known examples and predicts based on the k-nearest neighbours majority vote for a class.classKNearestNeighboursK nearest neighbour classification algorithm that is seeded with a "database" of known examples and predicts based on the k-nearest neighbours majority vote for a class.classSparseKNearestNeighboursK nearest neighbour classification algorithm that is seeded with a "database" of known examples and predicts based on the k-nearest neighbours majority vote for a class. -
Uses of Classifier in de.jungblut.classification.meta
Classes in de.jungblut.classification.meta with type parameters of type Classifier Modifier and Type Class Description classVoter<A extends Classifier>Implementation of vote ensembling.Classes in de.jungblut.classification.meta that implement Classifier Modifier and Type Class Description classVoter<A extends Classifier>Implementation of vote ensembling.Methods in de.jungblut.classification.meta with type parameters of type Classifier Modifier and Type Method Description static <K extends Classifier>
Voter<K>Voter. create(int numClassifiers, Voter.CombiningType type, ClassifierFactory<K> classifierFactory)Creates a new voting classificator.static <K extends Classifier>
Voter<K>Voter. fromTrainedModels(java.util.List<K> classifier)Creates a voter from the given trained models for prediction purposes.Methods in de.jungblut.classification.meta that return Classifier Modifier and Type Method Description Classifier[]Voter. getClassifier() -
Uses of Classifier in de.jungblut.classification.nn
Classes in de.jungblut.classification.nn that implement Classifier Modifier and Type Class Description classMultilayerPerceptronMultilayer perceptron implementation that works on GPU via JCuda and CPU. -
Uses of Classifier in de.jungblut.classification.regression
Classes in de.jungblut.classification.regression that implement Classifier Modifier and Type Class Description classLogisticRegression -
Uses of Classifier in de.jungblut.classification.tree
Classes in de.jungblut.classification.tree that implement Classifier Modifier and Type Class Description classDecisionTreeA decision tree that can be used for classification with numerical or categorical features.classRandomForestA decision tree forest, using bagging. -
Uses of Classifier in de.jungblut.ner
Classes in de.jungblut.ner that implement Classifier Modifier and Type Class Description classMaxEntMarkovModelMaximum entropy markov model for named entity recognition (classifying labels in sequence learning). -
Uses of Classifier in de.jungblut.nlp
Classes in de.jungblut.nlp that implement Classifier Modifier and Type Class Description classHMMHidden Markov Model implementation for multiple observations for all three types of problems HMM aims to solve (Decoding, likelihood estimation, unsupervised/supervised learning).
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