# Classes and Interfaces in #JavaML

_{# Classes and Interfaces in #JavaML - 214 results found.}

Name	Description	Type	Package	Framework
AbstractBayesianClassifier	Abstract Bayesian classifier (supervised).	Class	net.sf.javaml.classification.bayes	JavaML
AbstractBayesianClassifier_compact	Compact Abstract Bayesian classifier (supervised).	Class	net.sf.javaml.classification.bayes	JavaML
AbstractClassifier		Class	net.sf.javaml.classification	JavaML
AbstractCorrelation	Abstract super class for all correlation measures.	Class	net.sf.javaml.distance	JavaML
AbstractDistance	Abstract super class for all distance measures.	Class	net.sf.javaml.distance	JavaML
AbstractFilter	Umbrella class for filters that implements both the DatasetFilter interfaces.	Class	net.sf.javaml.filter	JavaML
AbstractInstance		Class	net.sf.javaml.core	JavaML
Abstraction		Class	net.sf.javaml.distance.fastdtw	JavaML
AbstractMeanClassifier	Abstract classifier class that is the parent of all classifiers that require the mean of each class as training.	Class	net.sf.javaml.classification	JavaML
AbstractSimilarity	Abstract super class for all similarity measures.	Class	net.sf.javaml.distance	JavaML
ActiveSetsOptimization	problem with only bounds constraints in multi-dimensions.	Class	net.sf.javaml.utils	JavaML
AICScore		Class	net.sf.javaml.clustering.evaluation	JavaML
AngularDistance		Class	net.sf.javaml.distance	JavaML
AQBC	This class implements the Adaptive Quality-based Clustering Algorithm, based on the implementation in MATLAB by De Smet et al.	Class	net.sf.javaml.clustering	JavaML
ARFFHandler	Provides method to load data from ARFF formatted files.	Class	net.sf.javaml.tools.data	JavaML
Arrays		Class	net.sf.javaml.distance.fastdtw.util	JavaML
ArrayUtils		Class	net.sf.javaml.utils	JavaML
Bagging	Bagging meta learner.	Class	net.sf.javaml.classification.meta	JavaML
Band		Class	net.sf.javaml.distance.fastdtw	JavaML
BICScore		Class	net.sf.javaml.clustering.evaluation	JavaML
CachedDistance	This class implements a wrapper around other distance measure to cache previously calculated distances.	Class	net.sf.javaml.distance	JavaML
CeilValueFilter	Filter to replace all values with their ceiled equivalent.	Class	net.sf.javaml.filter.instance	JavaML
ChebychevDistance		Class	net.sf.javaml.distance	JavaML
CIndex		Class	net.sf.javaml.clustering.evaluation	JavaML
ClassCounter	Data structure used for Bayesian networksAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.classification.bayes	JavaML
ClassCounter_compact	Data structure used for Entropy based algorithmsAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.classification.bayes	JavaML
Classifier	Interface for all classifiers.	Interface	net.sf.javaml.classification	JavaML
ClassRemoveFilter	Removes all instances from a data set that have a specific class valueVersion:0.	Class	net.sf.javaml.filter	JavaML
ClassReplaceFilter	Replaces a certain class value with another one.	Class	net.sf.javaml.filter	JavaML
ClassRetainFilter	Keeps all instances from a data set that have a specific class valueVersion:0.	Class	net.sf.javaml.filter	JavaML
Clusterer	A common interface for all clustering techniques.	Interface	net.sf.javaml.clustering	JavaML
ClusterEvaluation	This interface provides a frame for all measure that can be used to evaluate the quality of a clusterer.	Interface	net.sf.javaml.clustering.evaluation	JavaML
Cobweb	Class implementing the Cobweb and Classit clustering algorithms.	Class	net.sf.javaml.clustering	JavaML
ColMajorCell		Class	net.sf.javaml.distance.fastdtw.matrix	JavaML
Complex		Class	net.sf.javaml.core	JavaML
ConsistencyIndex	Consistency index for a pair of subsets.	Class	net.sf.javaml.distance	JavaML
ContingencyTables	Class implementing some statistical routines for contingency tables.	Class	net.sf.javaml.utils	JavaML
CosineDistance	This similarity based distance measure actually measures the angle between The value returned lies in the interval [0,1].	Class	net.sf.javaml.distance	JavaML
CosineSimilarity	This similarity based distance measure actually measures the angle between The value returned lies in the interval [0,1].	Class	net.sf.javaml.distance	JavaML
CrossValidation		Class	net.sf.javaml.classification.evaluation	JavaML
Dataset	Interface for a data set.	Interface	net.sf.javaml.core	JavaML
DatasetFilter	The interface for filters that can be applied on an When applying a filter to a data set it may modify the instances in the	Interface	net.sf.javaml.filter	JavaML
DatasetTools	This class provides utility methods on data sets.	Class	net.sf.javaml.tools	JavaML
DefaultDataset	Provides a standard data set implementation.	Class	net.sf.javaml.core	JavaML
DenseInstance	double array that provides a value for each attribute index.	Class	net.sf.javaml.core	JavaML
DensityBasedSpatialClustering	Provides the density-based-spatial-scanning clustering algorithm.	Class	net.sf.javaml.clustering	JavaML
DistanceMeasure	A distance measure is an algorithm to calculate the distance, similarity or correlation between two instances.	Interface	net.sf.javaml.distance	JavaML
DoubleFormat	DoubleFormat formats double numbers into a specified digit format.	Class	net.sf.javaml.clustering.mcl	JavaML
DTW		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
DTWSimilarity	A similarity measure based on "Dynamic Time Warping".	Class	net.sf.javaml.distance.dtw	JavaML
EqualWidthBinning	A filter that discretizes a range of numeric attributes in the data set into nominal attributes.	Class	net.sf.javaml.filter.discretize	JavaML
EuclideanDistance	This class implements the Euclidean distance.	Class	net.sf.javaml.distance	JavaML
EvaluateDataset	Tests a classifier on a data setAuthor:Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.classification.evaluation	JavaML
ExpandedResWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
ExpDouble	ExpDouble represents a double-precision number by a mantissa, a decimal exponent and the number of digits in the mantissa, in order to allow	Class	net.sf.javaml.clustering.mcl	JavaML
FarthestFirst	Cluster data using the FarthestFirst algorithm.	Class	net.sf.javaml.clustering	JavaML
FastDTW		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
FastDTW	Stan Salvador and Philip Chan, FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space, KDD Workshop on Mining Temporal and Sequential	Class	net.sf.javaml.distance.fastdtw	JavaML
FeatureRanking	Interface for algorithms that can generate an attribute ranking.	Interface	net.sf.javaml.featureselection	JavaML
FeatureScoring	Interface for all attribute evaluation methods.	Interface	net.sf.javaml.featureselection	JavaML
FeatureSelection	Top-level interface for feature selection algorithms.	Interface	net.sf.javaml.featureselection	JavaML
FeatureSubsetSelection	Interface for all attribute subset selection algorithms.	Interface	net.sf.javaml.featureselection	JavaML
FileHandler	A class to load data sets from file and write them back.	Class	net.sf.javaml.tools.data	JavaML
FloorValueFilter	Filter to replace all values with their rounded equivalentAuthor:Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.filter.instance	JavaML
FourBinMinimalEntropyPartitioning	A filter that discretizes a range of numeric attributes in the data set into 4 nominal attributes.	Class	net.sf.javaml.filter.discretize	JavaML
FromWekaUtils	Provides utility methods to convert data from the WEKA format to the Java-MLVersion:0.	Class	net.sf.javaml.tools.weka	JavaML
FullWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
GainRatio		Class	net.sf.javaml.featureselection.scoring	JavaML
Gamma		Class	net.sf.javaml.clustering.evaluation	JavaML
GammaFunction		Class	net.sf.javaml.utils	JavaML
GPlus		Class	net.sf.javaml.clustering.evaluation	JavaML
GreedyBackwardElimination	Provides an implementation of the backward greedy attribute subset elimination algorithm.	Class	net.sf.javaml.featureselection.subset	JavaML
GreedyForwardSelection	Provides an implementation of the forward greedy attribute subset selection.	Class	net.sf.javaml.featureselection.subset	JavaML
GridSearch	Helps finding optimal parameters C and gamma for the LibSVM Support Vector Machine.	Class	libsvm	JavaML
HybridCentroidSimilarity	H_2 from the Zhao 2001 paperAuthor:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
HybridPairwiseSimilarities	H_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
Instance	The interface for instances in a data set.	Interface	net.sf.javaml.core	JavaML
InstanceFilter	The interface for filters that can be applied on an Instance without the need for a reference	Interface	net.sf.javaml.filter	JavaML
InstanceNormalizeMidrange	This filter will normalize all the attributes in an instance to a certain interval determined by a mid-range and a range.	Class	net.sf.javaml.filter.normalize	JavaML
InstanceTools	Provides utility methods for manipulating, creating and modifying instances.	Class	net.sf.javaml.tools	JavaML
IterativeFarthestFirst		Class	net.sf.javaml.clustering	JavaML
IterativeKMeans	This class implements an extension of KMeans.	Class	net.sf.javaml.clustering	JavaML
IterativeMultiKMeans	This class implements an extension of KMeans, combining Iterative- en MultiKMeans.	Class	net.sf.javaml.clustering	JavaML
JaccardIndexDistance	Jaccard index.	Class	net.sf.javaml.distance	JavaML
JaccardIndexSimilarity	Jaccard index.	Class	net.sf.javaml.distance	JavaML
KDependentBayesClassifier		Class	net.sf.javaml.classification.bayes	JavaML
KDTree	KDTree is a class supporting KD-tree insertion, deletion, equality search, range search, and nearest neighbor(s) using double-precision floating-point	Class	net.sf.javaml.core.kdtree	JavaML
KDtreeKNN	KDtree support.	Class	net.sf.javaml.classification	JavaML
KMeans	J.	Class	net.sf.javaml.clustering	JavaML
KMedoids	algorithm that is very much like k-means.	Class	net.sf.javaml.clustering	JavaML
KNearestNeighbors		Class	net.sf.javaml.classification	JavaML
KNearestNeighbors	Replaces the missing value with the average of the values of its nearest This technique does not guarantee that all missing will be replaced.	Class	net.sf.javaml.filter.missingvalue	JavaML
KullbackLeiblerDivergence	Feature scoring algorithm based on Kullback-Leibler divergence of the value distributions of features.	Class	net.sf.javaml.featureselection.scoring	JavaML
LibSVM	Wrapper for the libSVM library by Chih-Chung Chang and Chih-Jen Lin.	Class	libsvm	JavaML
LinearKernel		Class	net.sf.javaml.distance	JavaML
LinearRankingEnsemble	Provides a linear aggregation feature selection ensemble as described in Saeys, Y.	Class	net.sf.javaml.featureselection.ensemble	JavaML
LinearWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
ListTools		Class	net.sf.javaml.tools	JavaML
LogLikelihoodFunction		Class	net.sf.javaml.utils	JavaML
MahalanobisDistance		Class	net.sf.javaml.distance	JavaML
ManhattanDistance	The Manhattan distance is the sum of the (absolute) differences of their coordinates.	Class	net.sf.javaml.distance	JavaML
MarkovClustering	MarkovClustering implements the Markov clustering (MCL) algorithm for graphs, using a HashMap-based sparse representation of a Markov matrix, i.	Class	net.sf.javaml.clustering.mcl	JavaML
MathUtils	A class that provides some utility math methods.	Class	net.sf.javaml.utils	JavaML
Matrix		Class	net.sf.javaml.matrix	JavaML
MaxProductSimilarity	Specialized similarity that takes the maximum product of two feature values.	Class	net.sf.javaml.distance	JavaML
MCL		Class	net.sf.javaml.clustering.mcl	JavaML
MeanFeatureVotingClassifier	This classifier calculates the mean for each class.	Class	net.sf.javaml.classification	JavaML
MinkowskiDistance		Class	net.sf.javaml.distance	JavaML
MinMaxCut	G_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
MissingClassFilter	Filters all instances from a data set that have their class value not setVersion:0.	Class	net.sf.javaml.filter	JavaML
MultiKMeans	This class implements an extension of KMeans (SKM).	Class	net.sf.javaml.clustering	JavaML
NaiveBayesClassifier		Class	net.sf.javaml.classification.bayes	JavaML
NearestMeanClassifier	Nearest mean classifier.	Class	net.sf.javaml.classification	JavaML
NormalizedEuclideanDistance	A normalized version of the Euclidean distance.	Class	net.sf.javaml.distance	JavaML
NormalizedEuclideanSimilarity		Class	net.sf.javaml.distance	JavaML
NormalizeMean	This filter will normalize the data set with mean 0 and standard deviation 1 The normalization will be done on the attributes, so each attribute will have	Class	net.sf.javaml.filter.normalize	JavaML
NormalizeMeanIQR135	This filter will normalize the data set with mean 0 and standard deviation 1 The normalization will be done on the attributes, so each attribute will have	Class	net.sf.javaml.filter.normalize	JavaML
NormalizeMidrange	This filter will normalize the data set with a certain mid-range and a certain range for each attribute.	Class	net.sf.javaml.filter.normalize	JavaML
NormDistance	The norm distance or This class implements the Norm distance.	Class	net.sf.javaml.distance	JavaML
PAA		Class	net.sf.javaml.distance.fastdtw.timeseries	JavaML
ParallelogramWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
PearsonCorrelationCoefficient	Calculates the Pearson Correlation Coeffient between two vectors.	Class	net.sf.javaml.distance	JavaML
PerformanceMeasure	Class implementing several performance measures commonly used for classification algorithms.	Class	net.sf.javaml.classification.evaluation	JavaML
PointBiserial		Class	net.sf.javaml.clustering.evaluation	JavaML
Polynomial	Polynomial functions.	Class	net.sf.javaml.utils	JavaML
PolynomialKernel		Class	net.sf.javaml.distance	JavaML
RandomForest		Class	net.sf.javaml.classification.tree	JavaML
RandomForestAttributeEvaluation	Random Forest based attribute evaluation.	Class	net.sf.javaml.featureselection.scoring	JavaML
RandomTree	Simple and fast implementation of the RandomTree classifier.	Class	net.sf.javaml.classification.tree	JavaML
RankingFromScoring	Creates an attribute ranking from an attribute evaluation technique.	Class	net.sf.javaml.featureselection.ranking	JavaML
RBFKernel	The kernel method for measuring similarities between instances.	Class	net.sf.javaml.distance	JavaML
RBFKernelDistance		Class	net.sf.javaml.distance	JavaML
RecursiveFeatureEliminationSVM	Starting with the full feature set, attributes are ranked according to the weights they get in a linear SVM.	Class	net.sf.javaml.featureselection.ranking	JavaML
RecursiveMinimalEntropyPartitioning	A filter that discretizes a range of numeric attributes in the data set into nominal attributes.	Class	net.sf.javaml.filter.discretize	JavaML
RELIEF	This implementation is extended to include more neighbors in calculating the weights of the features.	Class	net.sf.javaml.featureselection.scoring	JavaML
RemoveAttributes		Class	net.sf.javaml.filter	JavaML
RemoveMissingValue	Removes all instances that have missing values.	Class	net.sf.javaml.filter.missingvalue	JavaML
ReplaceValueFilter		Class	net.sf.javaml.filter.instance	JavaML
ReplaceWithValue	Replaces all Double.	Class	net.sf.javaml.filter.missingvalue	JavaML
RetainAttributes	Filter to retain a set of wanted attributes and remove all othersAuthor:Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.filter	JavaML
RoundValueFilter	Filter to replace all values with their rounded equivalentAuthor:Thomas Abeel (thomas@abeel.	Class	net.sf.javaml.filter.instance	JavaML
Sampling		Class	net.sf.javaml.sampling	JavaML
SamplingMethod	Defines sampling methods to select a subset of a set integers.	Class	net.sf.javaml.sampling	JavaML
SearchWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
SelfOptimizingLinearLibSVM	A svm variant the optimizes the C-paramater by itself.	Class	libsvm	JavaML
Serial	Class with utility methods for serialization.	Class	net.sf.javaml.tools	JavaML
SetTools		Class	net.sf.javaml.tools	JavaML
SimpleBagging	Bootstrap aggregating (Bagging) meta learner.	Class	net.sf.javaml.classification.meta	JavaML
SineWave		Class	net.sf.javaml.distance.fastdtw.timeseries	JavaML
SOM	Classifier based on the Self-organized map clustering.	Class	net.sf.javaml.classification	JavaML
SOM	An implementation of the Self Organizing Maps algorithm as proposed by This implementation is derived from the Bachelor thesis of Tomi Suuronen	Class	net.sf.javaml.clustering	JavaML
SparseInstance	indices to values.	Class	net.sf.javaml.core	JavaML
SparseMatrix	SparseMatrix is a sparse matrix with row-major format.	Class	net.sf.javaml.clustering.mcl	JavaML
SparseVector	SparseVector represents a sparse vector.	Class	net.sf.javaml.clustering.mcl	JavaML
SpearmanFootruleDistance		Class	net.sf.javaml.distance	JavaML
SpearmanRankCorrelation	Calculates the Spearman rank correlation of two instances.	Class	net.sf.javaml.distance	JavaML
SpecialFunctions	Class implementing some mathematical functions.	Class	net.sf.javaml.utils	JavaML
Statistics	Class implementing some distributions, tests, etc.	Class	net.sf.javaml.utils	JavaML
StreamHandler		Class	net.sf.javaml.tools.data	JavaML
SumOfAveragePairwiseSimilarities	I_1 from the Zhao 2001 paperAuthor:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
SumOfCentroidSimilarities	TODO uitleg I_2 from Zhao 2001Author:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
SumOfSquaredErrors	I_3 from the Zhao 2001 paperAuthor:Andreas De Rijcke	Class	net.sf.javaml.clustering.evaluation	JavaML
SymmetricalUncertainty		Class	net.sf.javaml.featureselection.scoring	JavaML
Tau		Class	net.sf.javaml.clustering.evaluation	JavaML
ThreeBinMinimalEntropyPartitioning	A filter that discretizes a range of numeric attributes in the data set into 3 nominal attributes.	Class	net.sf.javaml.filter.discretize	JavaML
TimeSeries		Class	net.sf.javaml.distance.fastdtw.timeseries	JavaML
TimeSeriesPoint		Class	net.sf.javaml.distance.fastdtw.timeseries	JavaML
TimeWarpInfo		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
ToWekaUtils	Provides utility methods to convert data to the WEKA format.	Class	net.sf.javaml.tools.weka	JavaML
TraceScatterMatrix	E_1 from the Zhao 2001 paper Distance measure has to be	Class	net.sf.javaml.clustering.evaluation	JavaML
TrainingRequiredException	Indicates that the algorithm that throws this exception should have been trained prior to point the exception was thrown.	Class	net.sf.javaml.core.exception	JavaML
Tutorial2BinMinimalEntropyPartitioning	Tutorial Two Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.filter	JavaML
Tutorial3BinMinimalEntropyPartitioning	Tutorial Three Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.filter	JavaML
Tutorial4BinMinimalEntropyPartitioning	Tutorial Four Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.filter	JavaML
TutorialARFFLoader	Demonstrates how you can load data from an ARFF formatted file.	Class	tutorials.tools	JavaML
TutorialClusterEvaluation	Shows how to use the different cluster evaluation measure that are implemented in Java-ML.	Class	tutorials.clustering	JavaML
TutorialCrossValidation	This tutorial shows how you can do cross-validation with Java-MLAuthor:Thomas Abeel (thomas@abeel.	Class	tutorials.classification	JavaML
TutorialCVSameFolds	This tutorial shows how you can do multiple cross-validations with the sameAuthor:Thomas Abeel (thomas@abeel.	Class	tutorials.classification	JavaML
TutorialData		Class	tutorials	JavaML
TutorialDataLoader	This tutorial shows how to load data from a local file.	Class	tutorials.tools	JavaML
TutorialDataset	This tutorial show how to create a Dataset from a collection of instances.	Class	tutorials.core	JavaML
TutorialDenseInstance	This tutorial shows the very first step in using Java-ML.	Class	tutorials.core	JavaML
TutorialEnsembleFeatureSelection	Tutorial to illustrate ensemble feature selection.	Class	tutorials.featureselection	JavaML
TutorialEvaluateDataset	This tutorial show how to use the EvaluateDataset class to test the performance of a classifier on a data set.	Class	tutorials.classification	JavaML
TutorialFeatureRanking		Class	tutorials.featureselection	JavaML
TutorialFeatureScoring		Class	tutorials.featureselection	JavaML
TutorialFeatureSubsetSelection	Shows the basic steps to create use a feature subset selection algorithm.	Class	tutorials.featureselection	JavaML
TutorialKDependentBayes	Tutorial for K Dependent Bayes classifierAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.classification	JavaML
TutorialKDtreeKNN	This tutorial show how to use a the k-nearest neighbors classifier.	Class	tutorials.classification	JavaML
TutorialKMeans	This tutorial shows how to use a clustering algorithm to cluster a data set.	Class	tutorials.clustering	JavaML
TutorialKNN	This tutorial show how to use a the k-nearest neighbors classifier.	Class	tutorials.classification	JavaML
TutorialLibSVM	This tutorial show how to use a the LibSVM classifier.	Class	tutorials.classification	JavaML
TutorialNaiveBayes	Tutorial for Naive Bayes classifierAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.classification	JavaML
TutorialRandomForest	Tutorial for the random forest classifier.	Class	tutorials.classification	JavaML
TutorialRecursiveMinimalEntropyPartitioning	Tutorial Recursive Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.	Class	tutorials.filter	JavaML
TutorialSampling	Sample program illustrating how to use sampling.	Class	tutorials.tools	JavaML
TutorialSelfOptimizingLibSVM	This tutorial show how to use a the LibSVM classifier.	Class	tutorials.classification	JavaML
TutorialSparseInstance	Shows how to create a SparseInstance.	Class	tutorials.core	JavaML
TutorialStoreData	Demonstrates how you can store data to a file.	Class	tutorials.tools	JavaML
TutorialWekaAttributeSelection	Tutorial how to use the Bridge to WEKA AS Evaluation , AS Search and Evaluator algorithms in Java-ML	Class	tutorials.featureselection	JavaML
TutorialWekaClassifier	Tutorial how to use a Weka classifier in Java-ML.	Class	tutorials.tools	JavaML
TutorialWekaClusterer	Tutorial how to use a Weka classifier in Java-ML.	Class	tutorials.tools	JavaML
TwoBinMinimalEntropyPartitioning	A filter that discretizes a range of numeric attributes in the data set into 2 nominal attributes.	Class	net.sf.javaml.filter.discretize	JavaML
TypeConversions		Class	net.sf.javaml.distance.fastdtw.lang	JavaML
UnsetClassFilter	Filter to remove class information from a data set or instance.	Class	net.sf.javaml.filter	JavaML
Vectors	Static vector manipulation routines for Matlab porting and other numeric operations.	Class	net.sf.javaml.clustering.mcl	JavaML
WarpPath		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
WarpPathWindow		Class	net.sf.javaml.distance.fastdtw.dtw	JavaML
WB		Class	net.sf.javaml.clustering.evaluation	JavaML
WekaAttributeSelection		Class	net.sf.javaml.tools.weka	JavaML
WekaClassifier		Class	net.sf.javaml.tools.weka	JavaML
WekaClusterer	Provides a bridge between Java-ML and the clustering algorithms in WEKA.	Class	net.sf.javaml.tools.weka	JavaML
WekaException	This exception should be thrown when something went wrong with calls to theVersion:0.	Class	net.sf.javaml.tools.weka	JavaML
ZeroR	ZeroR classifier implementation.	Class	net.sf.javaml.classification	JavaML

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