Package weka.classifiers.bayes

Examples of weka.classifiers.bayes.BayesNet.buildClassifier()


        String[] str = cls.getOptions();
     //   str[2] = "weka.classifiers.bayes.net.search.local.TAN";
     //   str[4] = "";
      //  str[5] = "";
        cls.setOptions(str);
      cls.buildClassifier(data);
    } catch (Exception e) {
      e.printStackTrace();
    }
   
    return cls;
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        BayesNet EmptyNet = new BayesNet();
        K2 oSearchAlgorithm = new K2();
        oSearchAlgorithm.setInitAsNaiveBayes(false);
        oSearchAlgorithm.setMaxNrOfParents(0);
        EmptyNet.setSearchAlgorithm(oSearchAlgorithm);
        EmptyNet.buildClassifier(instances);

        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
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        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
        NBNet.buildClassifier(instances);

        // estimate CPTs
        for (int iAttribute = 0; iAttribute < instances.numAttributes(); iAttribute++) {
            if (iAttribute != instances.classIndex()) {
                  double w1 = 0.0, w2 = 0.0;
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        BayesNet EmptyNet = new BayesNet();
        K2 oSearchAlgorithm = new K2();
        oSearchAlgorithm.setInitAsNaiveBayes(false);
        oSearchAlgorithm.setMaxNrOfParents(0);
        EmptyNet.setSearchAlgorithm(oSearchAlgorithm);
        EmptyNet.buildClassifier(instances);

        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
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        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
        NBNet.buildClassifier(instances);

        // estimate CPTs
        for (int iAttribute = 0; iAttribute < instances.numAttributes(); iAttribute++) {
            if (iAttribute != instances.classIndex()) {
                  double w1 = 0.0, w2 = 0.0;
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    try {
      BayesNet b = new BayesNet();
      b.setSearchAlgorithm( new ICSSearchAlgorithm());
      Instances instances = new Instances(new FileReader("C:\\eclipse\\workspace\\weka\\data\\contact-lenses.arff"));
      instances.setClassIndex(instances.numAttributes() - 1);
      b.buildClassifier(instances);
      System.out.println(b.toString());
    } catch (Exception e) {
      e.printStackTrace();
    }
  } // main
View Full Code Here

        BayesNet EmptyNet = new BayesNet();
        K2 oSearchAlgorithm = new K2();
        oSearchAlgorithm.setInitAsNaiveBayes(false);
        oSearchAlgorithm.setMaxNrOfParents(0);
        EmptyNet.setSearchAlgorithm(oSearchAlgorithm);
        EmptyNet.buildClassifier(instances);

        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
View Full Code Here

        BayesNet NBNet = new BayesNet();
        oSearchAlgorithm.setInitAsNaiveBayes(true);
        oSearchAlgorithm.setMaxNrOfParents(1);
        NBNet.setSearchAlgorithm(oSearchAlgorithm);
        NBNet.buildClassifier(instances);

        // estimate CPTs
        for (int iAttribute = 0; iAttribute < instances.numAttributes(); iAttribute++) {
            if (iAttribute != instances.classIndex()) {
                  double w1 = 0.0, w2 = 0.0;
View Full Code Here

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