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# Classes and Interfaces in #JavaML - 214 results found.
NameDescriptionTypePackageFrameworkJavaDoc
AbstractBayesianClassifierAbstract Bayesian classifier (supervised).Classnet.sf.javaml.classification.bayesJavaMLjavadoc
AbstractBayesianClassifier_compactCompact Abstract Bayesian classifier (supervised).Classnet.sf.javaml.classification.bayesJavaMLjavadoc
AbstractClassifierClassnet.sf.javaml.classificationJavaMLjavadoc
AbstractCorrelationAbstract super class for all correlation measures.Classnet.sf.javaml.distanceJavaMLjavadoc
AbstractDistanceAbstract super class for all distance measures.Classnet.sf.javaml.distanceJavaMLjavadoc
AbstractFilterUmbrella class for filters that implements both the DatasetFilter interfaces.Classnet.sf.javaml.filterJavaMLjavadoc
AbstractInstanceClassnet.sf.javaml.coreJavaMLjavadoc
AbstractionClassnet.sf.javaml.distance.fastdtwJavaMLjavadoc
AbstractMeanClassifierAbstract classifier class that is the parent of all classifiers that require the mean of each class as training.Classnet.sf.javaml.classificationJavaMLjavadoc
AbstractSimilarityAbstract super class for all similarity measures.Classnet.sf.javaml.distanceJavaMLjavadoc
ActiveSetsOptimization problem with only bounds constraints in multi-dimensions.Classnet.sf.javaml.utilsJavaMLjavadoc
AICScoreClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
AngularDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
AQBCThis class implements the Adaptive Quality-based Clustering Algorithm, based on the implementation in MATLAB by De Smet et al.Classnet.sf.javaml.clusteringJavaMLjavadoc
ARFFHandlerProvides method to load data from ARFF formatted files.Classnet.sf.javaml.tools.dataJavaMLjavadoc
ArraysClassnet.sf.javaml.distance.fastdtw.utilJavaMLjavadoc
ArrayUtilsClassnet.sf.javaml.utilsJavaMLjavadoc
BaggingBagging meta learner.Classnet.sf.javaml.classification.metaJavaMLjavadoc
BandClassnet.sf.javaml.distance.fastdtwJavaMLjavadoc
BICScoreClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
CachedDistanceThis class implements a wrapper around other distance measure to cache previously calculated distances.Classnet.sf.javaml.distanceJavaMLjavadoc
CeilValueFilterFilter to replace all values with their ceiled equivalent.Classnet.sf.javaml.filter.instanceJavaMLjavadoc
ChebychevDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
CIndexClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc

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ClassCounterData structure used for Bayesian networksAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classnet.sf.javaml.classification.bayesJavaMLjavadoc
ClassCounter_compactData structure used for Entropy based algorithmsAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classnet.sf.javaml.classification.bayesJavaMLjavadoc
ClassifierInterface for all classifiers.Interfacenet.sf.javaml.classificationJavaMLjavadoc
ClassRemoveFilterRemoves all instances from a data set that have a specific class valueVersion:0.Classnet.sf.javaml.filterJavaMLjavadoc
ClassReplaceFilterReplaces a certain class value with another one.Classnet.sf.javaml.filterJavaMLjavadoc
ClassRetainFilterKeeps all instances from a data set that have a specific class valueVersion:0.Classnet.sf.javaml.filterJavaMLjavadoc
ClustererA common interface for all clustering techniques.Interfacenet.sf.javaml.clusteringJavaMLjavadoc
ClusterEvaluationThis interface provides a frame for all measure that can be used to evaluate the quality of a clusterer.Interfacenet.sf.javaml.clustering.evaluationJavaMLjavadoc
CobwebClass implementing the Cobweb and Classit clustering algorithms.Classnet.sf.javaml.clusteringJavaMLjavadoc
ColMajorCellClassnet.sf.javaml.distance.fastdtw.matrixJavaMLjavadoc
ComplexClassnet.sf.javaml.coreJavaMLjavadoc
ConsistencyIndexConsistency index for a pair of subsets.Classnet.sf.javaml.distanceJavaMLjavadoc
ContingencyTablesClass implementing some statistical routines for contingency tables.Classnet.sf.javaml.utilsJavaMLjavadoc
CosineDistanceThis similarity based distance measure actually measures the angle between The value returned lies in the interval [0,1].Classnet.sf.javaml.distanceJavaMLjavadoc
CosineSimilarityThis similarity based distance measure actually measures the angle between The value returned lies in the interval [0,1].Classnet.sf.javaml.distanceJavaMLjavadoc
CrossValidationClassnet.sf.javaml.classification.evaluationJavaMLjavadoc
DatasetInterface for a data set.Interfacenet.sf.javaml.coreJavaMLjavadoc
DatasetFilterThe interface for filters that can be applied on an When applying a filter to a data set it may modify the instances in theInterfacenet.sf.javaml.filterJavaMLjavadoc
DatasetToolsThis class provides utility methods on data sets.Classnet.sf.javaml.toolsJavaMLjavadoc
DefaultDatasetProvides a standard data set implementation.Classnet.sf.javaml.coreJavaMLjavadoc
DenseInstance double array that provides a value for each attribute index.Classnet.sf.javaml.coreJavaMLjavadoc
DensityBasedSpatialClusteringProvides the density-based-spatial-scanning clustering algorithm.Classnet.sf.javaml.clusteringJavaMLjavadoc
DistanceMeasureA distance measure is an algorithm to calculate the distance, similarity or correlation between two instances.Interfacenet.sf.javaml.distanceJavaMLjavadoc
DoubleFormatDoubleFormat formats double numbers into a specified digit format.Classnet.sf.javaml.clustering.mclJavaMLjavadoc
DTWClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc

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DTWSimilarityA similarity measure based on "Dynamic Time Warping".Classnet.sf.javaml.distance.dtwJavaMLjavadoc
EqualWidthBinningA filter that discretizes a range of numeric attributes in the data set into nominal attributes.Classnet.sf.javaml.filter.discretizeJavaMLjavadoc
EuclideanDistanceThis class implements the Euclidean distance.Classnet.sf.javaml.distanceJavaMLjavadoc
EvaluateDatasetTests a classifier on a data setAuthor:Thomas Abeel (thomas@abeel.Classnet.sf.javaml.classification.evaluationJavaMLjavadoc
ExpandedResWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
ExpDoubleExpDouble represents a double-precision number by a mantissa, a decimal exponent and the number of digits in the mantissa, in order to allowClassnet.sf.javaml.clustering.mclJavaMLjavadoc
FarthestFirstCluster data using the FarthestFirst algorithm.Classnet.sf.javaml.clusteringJavaMLjavadoc
FastDTWClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
FastDTW Stan Salvador and Philip Chan, FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space, KDD Workshop on Mining Temporal and SequentialClassnet.sf.javaml.distance.fastdtwJavaMLjavadoc
FeatureRankingInterface for algorithms that can generate an attribute ranking.Interfacenet.sf.javaml.featureselectionJavaMLjavadoc
FeatureScoringInterface for all attribute evaluation methods.Interfacenet.sf.javaml.featureselectionJavaMLjavadoc
FeatureSelectionTop-level interface for feature selection algorithms.Interfacenet.sf.javaml.featureselectionJavaMLjavadoc
FeatureSubsetSelectionInterface for all attribute subset selection algorithms.Interfacenet.sf.javaml.featureselectionJavaMLjavadoc
FileHandlerA class to load data sets from file and write them back.Classnet.sf.javaml.tools.dataJavaMLjavadoc
FloorValueFilterFilter to replace all values with their rounded equivalentAuthor:Thomas Abeel (thomas@abeel.Classnet.sf.javaml.filter.instanceJavaMLjavadoc
FourBinMinimalEntropyPartitioningA filter that discretizes a range of numeric attributes in the data set into 4 nominal attributes.Classnet.sf.javaml.filter.discretizeJavaMLjavadoc
FromWekaUtilsProvides utility methods to convert data from the WEKA format to the Java-MLVersion:0.Classnet.sf.javaml.tools.wekaJavaMLjavadoc
FullWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
GainRatioClassnet.sf.javaml.featureselection.scoringJavaMLjavadoc
GammaClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
GammaFunctionClassnet.sf.javaml.utilsJavaMLjavadoc
GPlusClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
GreedyBackwardEliminationProvides an implementation of the backward greedy attribute subset elimination algorithm.Classnet.sf.javaml.featureselection.subsetJavaMLjavadoc
GreedyForwardSelectionProvides an implementation of the forward greedy attribute subset selection.Classnet.sf.javaml.featureselection.subsetJavaMLjavadoc
GridSearchHelps finding optimal parameters C and gamma for the LibSVM Support Vector Machine.ClasslibsvmJavaMLjavadoc

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HybridCentroidSimilarityH_2 from the Zhao 2001 paperAuthor:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
HybridPairwiseSimilaritiesH_1 from the Zhao 2001 paperAuthor:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
InstanceThe interface for instances in a data set.Interfacenet.sf.javaml.coreJavaMLjavadoc
InstanceFilterThe interface for filters that can be applied on an Instance without the need for a referenceInterfacenet.sf.javaml.filterJavaMLjavadoc
InstanceNormalizeMidrangeThis filter will normalize all the attributes in an instance to a certain interval determined by a mid-range and a range.Classnet.sf.javaml.filter.normalizeJavaMLjavadoc
InstanceToolsProvides utility methods for manipulating, creating and modifying instances.Classnet.sf.javaml.toolsJavaMLjavadoc
IterativeFarthestFirstClassnet.sf.javaml.clusteringJavaMLjavadoc
IterativeKMeansThis class implements an extension of KMeans.Classnet.sf.javaml.clusteringJavaMLjavadoc
IterativeMultiKMeansThis class implements an extension of KMeans, combining Iterative- en MultiKMeans.Classnet.sf.javaml.clusteringJavaMLjavadoc
JaccardIndexDistanceJaccard index.Classnet.sf.javaml.distanceJavaMLjavadoc
JaccardIndexSimilarityJaccard index.Classnet.sf.javaml.distanceJavaMLjavadoc
KDependentBayesClassifierClassnet.sf.javaml.classification.bayesJavaMLjavadoc
KDTreeKDTree is a class supporting KD-tree insertion, deletion, equality search, range search, and nearest neighbor(s) using double-precision floating-pointClassnet.sf.javaml.core.kdtreeJavaMLjavadoc
KDtreeKNN KDtree support.Classnet.sf.javaml.classificationJavaMLjavadoc
KMeans J.Classnet.sf.javaml.clusteringJavaMLjavadoc
KMedoids algorithm that is very much like k-means.Classnet.sf.javaml.clusteringJavaMLjavadoc
KNearestNeighborsClassnet.sf.javaml.classificationJavaMLjavadoc
KNearestNeighborsReplaces the missing value with the average of the values of its nearest This technique does not guarantee that all missing will be replaced.Classnet.sf.javaml.filter.missingvalueJavaMLjavadoc
KullbackLeiblerDivergenceFeature scoring algorithm based on Kullback-Leibler divergence of the value distributions of features.Classnet.sf.javaml.featureselection.scoringJavaMLjavadoc
LibSVMWrapper for the libSVM library by Chih-Chung Chang and Chih-Jen Lin.ClasslibsvmJavaMLjavadoc
LinearKernelClassnet.sf.javaml.distanceJavaMLjavadoc
LinearRankingEnsembleProvides a linear aggregation feature selection ensemble as described in Saeys, Y.Classnet.sf.javaml.featureselection.ensembleJavaMLjavadoc
LinearWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
ListToolsClassnet.sf.javaml.toolsJavaMLjavadoc
LogLikelihoodFunctionClassnet.sf.javaml.utilsJavaMLjavadoc

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MahalanobisDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
ManhattanDistanceThe Manhattan distance is the sum of the (absolute) differences of their coordinates.Classnet.sf.javaml.distanceJavaMLjavadoc
MarkovClusteringMarkovClustering implements the Markov clustering (MCL) algorithm for graphs, using a HashMap-based sparse representation of a Markov matrix, i.Classnet.sf.javaml.clustering.mclJavaMLjavadoc
MathUtilsA class that provides some utility math methods.Classnet.sf.javaml.utilsJavaMLjavadoc
MatrixClassnet.sf.javaml.matrixJavaMLjavadoc
MaxProductSimilaritySpecialized similarity that takes the maximum product of two feature values.Classnet.sf.javaml.distanceJavaMLjavadoc
MCLClassnet.sf.javaml.clustering.mclJavaMLjavadoc
MeanFeatureVotingClassifierThis classifier calculates the mean for each class.Classnet.sf.javaml.classificationJavaMLjavadoc
MinkowskiDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
MinMaxCutG_1 from the Zhao 2001 paperAuthor:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
MissingClassFilterFilters all instances from a data set that have their class value not setVersion:0.Classnet.sf.javaml.filterJavaMLjavadoc
MultiKMeansThis class implements an extension of KMeans (SKM).Classnet.sf.javaml.clusteringJavaMLjavadoc
NaiveBayesClassifierClassnet.sf.javaml.classification.bayesJavaMLjavadoc
NearestMeanClassifierNearest mean classifier.Classnet.sf.javaml.classificationJavaMLjavadoc
NormalizedEuclideanDistanceA normalized version of the Euclidean distance.Classnet.sf.javaml.distanceJavaMLjavadoc
NormalizedEuclideanSimilarityClassnet.sf.javaml.distanceJavaMLjavadoc
NormalizeMeanThis 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 haveClassnet.sf.javaml.filter.normalizeJavaMLjavadoc
NormalizeMeanIQR135This 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 haveClassnet.sf.javaml.filter.normalizeJavaMLjavadoc
NormalizeMidrangeThis filter will normalize the data set with a certain mid-range and a certain range for each attribute.Classnet.sf.javaml.filter.normalizeJavaMLjavadoc
NormDistanceThe norm distance or This class implements the Norm distance.Classnet.sf.javaml.distanceJavaMLjavadoc
PAAClassnet.sf.javaml.distance.fastdtw.timeseriesJavaMLjavadoc
ParallelogramWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
PearsonCorrelationCoefficientCalculates the Pearson Correlation Coeffient between two vectors.Classnet.sf.javaml.distanceJavaMLjavadoc
PerformanceMeasureClass implementing several performance measures commonly used for classification algorithms.Classnet.sf.javaml.classification.evaluationJavaMLjavadoc
PointBiserialClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc

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PolynomialPolynomial functions.Classnet.sf.javaml.utilsJavaMLjavadoc
PolynomialKernelClassnet.sf.javaml.distanceJavaMLjavadoc
RandomForestClassnet.sf.javaml.classification.treeJavaMLjavadoc
RandomForestAttributeEvaluationRandom Forest based attribute evaluation.Classnet.sf.javaml.featureselection.scoringJavaMLjavadoc
RandomTreeSimple and fast implementation of the RandomTree classifier.Classnet.sf.javaml.classification.treeJavaMLjavadoc
RankingFromScoringCreates an attribute ranking from an attribute evaluation technique.Classnet.sf.javaml.featureselection.rankingJavaMLjavadoc
RBFKernelThe kernel method for measuring similarities between instances.Classnet.sf.javaml.distanceJavaMLjavadoc
RBFKernelDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
RecursiveFeatureEliminationSVM Starting with the full feature set, attributes are ranked according to the weights they get in a linear SVM.Classnet.sf.javaml.featureselection.rankingJavaMLjavadoc
RecursiveMinimalEntropyPartitioningA filter that discretizes a range of numeric attributes in the data set into nominal attributes.Classnet.sf.javaml.filter.discretizeJavaMLjavadoc
RELIEF This implementation is extended to include more neighbors in calculating the weights of the features.Classnet.sf.javaml.featureselection.scoringJavaMLjavadoc
RemoveAttributesClassnet.sf.javaml.filterJavaMLjavadoc
RemoveMissingValueRemoves all instances that have missing values.Classnet.sf.javaml.filter.missingvalueJavaMLjavadoc
ReplaceValueFilterClassnet.sf.javaml.filter.instanceJavaMLjavadoc
ReplaceWithValueReplaces all Double.Classnet.sf.javaml.filter.missingvalueJavaMLjavadoc
RetainAttributesFilter to retain a set of wanted attributes and remove all othersAuthor:Thomas Abeel (thomas@abeel.Classnet.sf.javaml.filterJavaMLjavadoc
RoundValueFilterFilter to replace all values with their rounded equivalentAuthor:Thomas Abeel (thomas@abeel.Classnet.sf.javaml.filter.instanceJavaMLjavadoc
SamplingClassnet.sf.javaml.samplingJavaMLjavadoc
SamplingMethodDefines sampling methods to select a subset of a set integers.Classnet.sf.javaml.samplingJavaMLjavadoc
SearchWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
SelfOptimizingLinearLibSVMA svm variant the optimizes the C-paramater by itself.ClasslibsvmJavaMLjavadoc
SerialClass with utility methods for serialization.Classnet.sf.javaml.toolsJavaMLjavadoc
SetToolsClassnet.sf.javaml.toolsJavaMLjavadoc
SimpleBaggingBootstrap aggregating (Bagging) meta learner.Classnet.sf.javaml.classification.metaJavaMLjavadoc
SineWaveClassnet.sf.javaml.distance.fastdtw.timeseriesJavaMLjavadoc

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SOMClassifier based on the Self-organized map clustering.Classnet.sf.javaml.classificationJavaMLjavadoc
SOMAn implementation of the Self Organizing Maps algorithm as proposed by This implementation is derived from the Bachelor thesis of Tomi SuuronenClassnet.sf.javaml.clusteringJavaMLjavadoc
SparseInstance indices to values.Classnet.sf.javaml.coreJavaMLjavadoc
SparseMatrixSparseMatrix is a sparse matrix with row-major format.Classnet.sf.javaml.clustering.mclJavaMLjavadoc
SparseVectorSparseVector represents a sparse vector.Classnet.sf.javaml.clustering.mclJavaMLjavadoc
SpearmanFootruleDistanceClassnet.sf.javaml.distanceJavaMLjavadoc
SpearmanRankCorrelationCalculates the Spearman rank correlation of two instances.Classnet.sf.javaml.distanceJavaMLjavadoc
SpecialFunctionsClass implementing some mathematical functions.Classnet.sf.javaml.utilsJavaMLjavadoc
StatisticsClass implementing some distributions, tests, etc.Classnet.sf.javaml.utilsJavaMLjavadoc
StreamHandlerClassnet.sf.javaml.tools.dataJavaMLjavadoc
SumOfAveragePairwiseSimilaritiesI_1 from the Zhao 2001 paperAuthor:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
SumOfCentroidSimilaritiesTODO uitleg I_2 from Zhao 2001Author:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
SumOfSquaredErrorsI_3 from the Zhao 2001 paperAuthor:Andreas De RijckeClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
SymmetricalUncertaintyClassnet.sf.javaml.featureselection.scoringJavaMLjavadoc
TauClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
ThreeBinMinimalEntropyPartitioningA filter that discretizes a range of numeric attributes in the data set into 3 nominal attributes.Classnet.sf.javaml.filter.discretizeJavaMLjavadoc
TimeSeriesClassnet.sf.javaml.distance.fastdtw.timeseriesJavaMLjavadoc
TimeSeriesPointClassnet.sf.javaml.distance.fastdtw.timeseriesJavaMLjavadoc
TimeWarpInfoClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
ToWekaUtilsProvides utility methods to convert data to the WEKA format.Classnet.sf.javaml.tools.wekaJavaMLjavadoc
TraceScatterMatrixE_1 from the Zhao 2001 paper Distance measure has to beClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
TrainingRequiredExceptionIndicates that the algorithm that throws this exception should have been trained prior to point the exception was thrown.Classnet.sf.javaml.core.exceptionJavaMLjavadoc
Tutorial2BinMinimalEntropyPartitioningTutorial Two Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.filterJavaMLjavadoc
Tutorial3BinMinimalEntropyPartitioningTutorial Three Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.filterJavaMLjavadoc
Tutorial4BinMinimalEntropyPartitioningTutorial Four Bin Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.filterJavaMLjavadoc

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TutorialARFFLoaderDemonstrates how you can load data from an ARFF formatted file.Classtutorials.toolsJavaMLjavadoc
TutorialClusterEvaluationShows how to use the different cluster evaluation measure that are implemented in Java-ML.Classtutorials.clusteringJavaMLjavadoc
TutorialCrossValidationThis tutorial shows how you can do cross-validation with Java-MLAuthor:Thomas Abeel (thomas@abeel.Classtutorials.classificationJavaMLjavadoc
TutorialCVSameFoldsThis tutorial shows how you can do multiple cross-validations with the sameAuthor:Thomas Abeel (thomas@abeel.Classtutorials.classificationJavaMLjavadoc
TutorialDataClasstutorialsJavaMLjavadoc
TutorialDataLoaderThis tutorial shows how to load data from a local file.Classtutorials.toolsJavaMLjavadoc
TutorialDatasetThis tutorial show how to create a Dataset from a collection of instances.Classtutorials.coreJavaMLjavadoc
TutorialDenseInstanceThis tutorial shows the very first step in using Java-ML.Classtutorials.coreJavaMLjavadoc
TutorialEnsembleFeatureSelectionTutorial to illustrate ensemble feature selection.Classtutorials.featureselectionJavaMLjavadoc
TutorialEvaluateDatasetThis tutorial show how to use the EvaluateDataset class to test the performance of a classifier on a data set.Classtutorials.classificationJavaMLjavadoc
TutorialFeatureRankingClasstutorials.featureselectionJavaMLjavadoc
TutorialFeatureScoringClasstutorials.featureselectionJavaMLjavadoc
TutorialFeatureSubsetSelectionShows the basic steps to create use a feature subset selection algorithm.Classtutorials.featureselectionJavaMLjavadoc
TutorialKDependentBayesTutorial for K Dependent Bayes classifierAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.classificationJavaMLjavadoc
TutorialKDtreeKNNThis tutorial show how to use a the k-nearest neighbors classifier.Classtutorials.classificationJavaMLjavadoc
TutorialKMeansThis tutorial shows how to use a clustering algorithm to cluster a data set.Classtutorials.clusteringJavaMLjavadoc
TutorialKNNThis tutorial show how to use a the k-nearest neighbors classifier.Classtutorials.classificationJavaMLjavadoc
TutorialLibSVMThis tutorial show how to use a the LibSVM classifier.Classtutorials.classificationJavaMLjavadoc
TutorialNaiveBayesTutorial for Naive Bayes classifierAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.classificationJavaMLjavadoc
TutorialRandomForestTutorial for the random forest classifier.Classtutorials.classificationJavaMLjavadoc
TutorialRecursiveMinimalEntropyPartitioningTutorial Recursive Minimal Entropy PartitioningAuthor:Lieven Baeyens, Thomas Abeel (thomas@abeel.Classtutorials.filterJavaMLjavadoc
TutorialSamplingSample program illustrating how to use sampling.Classtutorials.toolsJavaMLjavadoc
TutorialSelfOptimizingLibSVMThis tutorial show how to use a the LibSVM classifier.Classtutorials.classificationJavaMLjavadoc
TutorialSparseInstanceShows how to create a SparseInstance.Classtutorials.coreJavaMLjavadoc
TutorialStoreDataDemonstrates how you can store data to a file.Classtutorials.toolsJavaMLjavadoc

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TutorialWekaAttributeSelectionTutorial how to use the Bridge to WEKA AS Evaluation , AS Search and Evaluator algorithms in Java-MLClasstutorials.featureselectionJavaMLjavadoc
TutorialWekaClassifierTutorial how to use a Weka classifier in Java-ML.Classtutorials.toolsJavaMLjavadoc
TutorialWekaClustererTutorial how to use a Weka classifier in Java-ML.Classtutorials.toolsJavaMLjavadoc
TwoBinMinimalEntropyPartitioningA filter that discretizes a range of numeric attributes in the data set into 2 nominal attributes.Classnet.sf.javaml.filter.discretizeJavaMLjavadoc
TypeConversionsClassnet.sf.javaml.distance.fastdtw.langJavaMLjavadoc
UnsetClassFilterFilter to remove class information from a data set or instance.Classnet.sf.javaml.filterJavaMLjavadoc
VectorsStatic vector manipulation routines for Matlab porting and other numeric operations.Classnet.sf.javaml.clustering.mclJavaMLjavadoc
WarpPathClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
WarpPathWindowClassnet.sf.javaml.distance.fastdtw.dtwJavaMLjavadoc
WBClassnet.sf.javaml.clustering.evaluationJavaMLjavadoc
WekaAttributeSelectionClassnet.sf.javaml.tools.wekaJavaMLjavadoc
WekaClassifierClassnet.sf.javaml.tools.wekaJavaMLjavadoc
WekaClustererProvides a bridge between Java-ML and the clustering algorithms in WEKA.Classnet.sf.javaml.tools.wekaJavaMLjavadoc
WekaExceptionThis exception should be thrown when something went wrong with calls to theVersion:0.Classnet.sf.javaml.tools.wekaJavaMLjavadoc
ZeroRZeroR classifier implementation.Classnet.sf.javaml.classificationJavaMLjavadoc

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