weka

  1. RandomForest

    This is the RandomForest classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/trees/RandomForest.html

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  2. Weka Classification

    This is the main algorithm that all of the Weka classification algorithms call.

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  3. WekaHierarchicalClusterer

    Uses Hierarchical clusterer, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/clusterers/HierarchicalClusterer.html

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  4. BayesianLogisticRegression

    This is the BayesianLogisticRegression classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/bayes/BayesianLogisticRegression.html

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  5. BayesNet

    This is the BayesNet classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/bayes/BayesNet.html

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  1. Weka Classification

    This is the main algorithm that all of the Weka classification algorithms call.

    weka
  2. RandomForest

    This is the RandomForest classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/trees/RandomForest.html

    weka
  3. NaiveBayes

    This is the NaiveBayes classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/bayes/NaiveBayes.html

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  4. KStar

    This is the KStar classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/lazy/KStar.html

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  5. BayesianLogisticRegression

    This is the BayesianLogisticRegression classifier, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/classifiers/bayes/BayesianLogisticRegression.html

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  1. CobwebClusterer

    Uses Cobweb clusterer, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/clusterers/Cobweb.html

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  2. CLOPEClusterer

    Uses CLOPE clusterer, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/clusterers/CLOPE.html

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  3. EMClusterer

    Uses EM clusterer, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/clusterers/EM.html

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  4. FarthestFirstClusterer

    Uses Farthest First clusterer, as implemented in Weka: http://weka.sourceforge.net/doc.stable/weka/clusterers/FarthestFirst.html

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Rows per page: 1-5 of 100