Repository /Weka/weka-3.6.1-src.jar

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Description

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Weka is covered by GNU General Public License.

See Weka homepage for more information.

Example algorithms from Weka that can be evaluated with RegressionTT70 evaluation procedure:

• weka.classifiers.functions.GaussianProcesses
• weka.classifiers.functions.IsotonicRegression
• weka.classifiers.functions.LeastMedSq
• weka.classifiers.functions.LinearRegression
• weka.classifiers.functions.MultilayerPerceptron
• weka.classifiers.functions.PaceRegression
• weka.classifiers.functions.RBFNetwork
• weka.classifiers.functions.SMOreg
• weka.classifiers.lazy.KStar
• weka.classifiers.lazy.LWL
• weka.classifiers.meta.AdditiveRegression
• weka.classifiers.meta.Bagging
• weka.classifiers.meta.RandomSubSpace
• weka.classifiers.meta.RegressionByDiscretization
• weka.classifiers.rules.ConjunctiveRule
• weka.classifiers.rules.DecisionTable
• weka.classifiers.rules.ZeroR
• weka.classifiers.trees.DecisionStump
• weka.classifiers.trees.REPTree

Example classification algorithms from Weka that can be evaluated with ClassificationTT70 evaluation procedure:

• weka.classifiers.bayes.AODE
• weka.classifiers.bayes.AODEsr
• weka.classifiers.bayes.ComplementNaiveBayes
• weka.classifiers.bayes.NaiveBayes
• weka.classifiers.bayes.NaiveBayesSimple
• weka.classifiers.functions.Logistic
• weka.classifiers.functions.MultilayerPerceptron
• weka.classifiers.functions.RBFNetwork
• weka.classifiers.functions.SMO
• weka.classifiers.functions.VotedPerceptron
• weka.classifiers.functions.Winnow
• weka.classifiers.lazy.IB1
• weka.classifiers.lazy.KStar
• weka.classifiers.lazy.LBR
• weka.classifiers.lazy.LWL
• weka.classifiers.meta.AdaBoostM1
• weka.classifiers.meta.AttributeSelectedClassifier
• weka.classifiers.meta.Bagging
• weka.classifiers.meta.ClassificationViaClustering
• weka.classifiers.meta.ClassificationViaRegression
• weka.classifiers.meta.Dagging
• weka.classifiers.meta.Decorate
• weka.classifiers.meta.END
• weka.classifiers.meta.FilteredClassifier
• weka.classifiers.meta.LogitBoost
• weka.classifiers.meta.MultiBoostAB
• weka.classifiers.meta.MultiClassClassifier
• weka.classifiers.meta.OrdinalClassClassifier
• weka.classifiers.meta.RacedIncrementalLogitBoost
• weka.classifiers.meta.RandomCommittee
• weka.classifiers.meta.RandomSubSpace
• weka.classifiers.meta.RotationForest
• weka.classifiers.meta.ThresholdSelector
• weka.classifiers.misc.HyperPipes
• weka.classifiers.misc.VFI
• weka.classifiers.rules.ConjunctiveRule
• weka.classifiers.rules.DTNB
• weka.classifiers.rules.DecisionTable
• weka.classifiers.rules.NNge
• weka.classifiers.rules.OneR
• weka.classifiers.rules.PART
• weka.classifiers.rules.Ridor
• weka.classifiers.rules.ZeroR
• weka.classifiers.trees.ADTree
• weka.classifiers.trees.BFTree
• weka.classifiers.trees.DecisionStump
• weka.classifiers.trees.FT
• weka.classifiers.trees.J48
• weka.classifiers.trees.J48graft
• weka.classifiers.trees.LADTree
• weka.classifiers.trees.LMT
• weka.classifiers.trees.NBTree
• weka.classifiers.trees.REPTree
• weka.classifiers.trees.RandomForest
• weka.classifiers.trees.RandomTree
• weka.classifiers.trees.SimpleCart