Package cc.mallet.types
Fundamental MALLET types, including FeatureVector, Instance, Label etc.
See: Description
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Interface Summary Interface Description AlphabetCarrying An interface for objects that contain one or more Alphabets.CachedMetric Stores a hash for each object being compared for efficient computation.ConstantMatrix Labeler Labeling A distribution over possible labels for an instance.Matrix Metric PartiallyRankedFeatureVector.Factory PartiallyRankedFeatureVector.PerLabelFactory PropertyHolder Author: saunders Created Nov 15, 2005 Copyright (C) Univ.RankedFeatureVector.Factory RankedFeatureVector.PerLabelFactory Sequence<E> Vector Deprecated -
Class Summary Class Description Alphabet A mapping between integers and objects where the mapping in each direction is efficient.AlphabetFactory ArrayListSequence<E> ArraySequence<E> AugmentableFeatureVector BiNormalSeparation Bi-Normal Separation is a feature weighting algorithm introduced in: An Extensive Empirical Study of Feature Selection Metrics for Text Classification, George Forman, Journal of Machine Learning Research, 3:1289--1305, 2003.BiNormalSeparation.Factory Factory class.ChainedInstanceIterator Deprecated CrossValidationIterator An iterator which splits anInstanceListinto n-folds and iterates over the folds for use in n-fold cross-validation.DenseMatrix DenseVector Dirichlet Various useful functions related to Dirichlet distributions.Dirichlet.Estimator Dirichlet.MethodOfMomentsEstimator EuclideanDistance ExpGain ExpGain.Factory FeatureConjunction FeatureConjunction.List FeatureCounter Efficient, compact, incremental counting of features in an alphabet.FeatureCounts FeatureCounts.Factory FeatureInducer FeatureSelection FeatureSelector FeatureSequence An implementation ofSequencethat ensures that every Object in the sequence has the same class.FeatureSequenceWithBigrams A FeatureSequence with a parallel record of bigrams, kept in a separate dictionaryFeatureVector A subset of anAlphabetin which each element of the subset has an associated value.FeatureVectorSequence GainRatio List of features along with their thresholds sorted in descending order of the ratio of (1) information gained by splitting instances on the feature at its associated threshold value, to (2) the split information.GradientGain GradientGain.Factory HashedSparseVector IDSorter This class is contains a comparator for use in sorting integers that have associated floating point values.IndexedSparseVector InfiniteDistance InfoGain InfoGain.Factory Instance A machine learning "example" to be used in training, testing or performance of various machine learning algorithms.InstanceList A list of machine learning instances, typically used for training or testing of a machine learning algorithm.InstanceListTUI InvertedIndex KLGain Label LabelAlphabet A mapping from arbitrary objects (usually String's) to integers (and corresponding Label objects) and back.Labelings A collection of labelings, either for a multi-label problem (all labels are part of the same label dictionary), or a factorized labeling, (each label is part of a different dictionary).Labels Usually some distribution over possible labels for an instance.LabelSequence LabelsSequence A simpleSequenceimplementation where all of the elements must be Labels.LabelVector LogNumber ManhattenDistance Matrix2 Deprecated Matrixn Implementation of Matrix that allows arbitrary number of dimensions.MatrixOps A class of static utility functions for manipulating arrays of double.Minkowski MultiInstanceList An implementation of InstanceList that logically combines multiple instance lists so that they appear as one list without copying the original lists.Multinomial A probability distribution over a set of features represented as aFeatureVector.Multinomial.Estimator A hierarchy of classes used to produce estimates of probabilities, in the form of a Multinomial, from counts associated with the elements of an Alphabet.Multinomial.LaplaceEstimator An MEstimator with m set to 1.Multinomial.Logged A Multinomial in which the values associated with each feature index fi is Math.log(probability[fi]) instead of probability[fi].Multinomial.MAPEstimator Unimplemented, but the MEstimators are.Multinomial.MEstimator An Estimator in which probability estimates in a Multinomial are generated by adding a constant m (specified at construction time) to each count before dividing by the total of the m-biased counts.Multinomial.MLEstimator An MEstimator with m set to 0.NormalizedDotProductMetric Computes 1 - [NullLabel Object that carries a LabelAlphabet.PagedInstanceList An InstanceList which avoids OutOfMemoryErrors by saving Instances to disk when there is not enough memory to create a new Instance.PartiallyRankedFeatureVector PerLabelFeatureCounts PerLabelFeatureCounts.Factory PerLabelInfoGain PerLabelInfoGain.Factory RankedFeatureVector ROCData Tracks ROC data for instances inTrialresults.SequencePair<I,O> SequencePairAlignment<I,O> SingleInstanceIterator SparseMatrixn Implementation of Matrix that allows arbitrary number of dimensions.SparseVector A vector that allocates memory only for non-zero values.StringEditFeatureVectorSequence StringEditVector StringKernel Computes a similarity metric between two strings, based on counts of common subsequences of characters.Token A representation of a piece of text, usually a single word, to which we can attach properties.TokenSequence A representation of a piece of text, usually a single word, to which we can attach properties.
Package cc.mallet.types Description
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