List of buildClusterer() Examples

Examples of buildClusterer()

weka.clusterers.AbstractClusterer.buildClusterer()
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options. @param data set of instances serving as training data @exception Exception if the clusterer has not been generated successfully
weka.clusterers.EM.buildClusterer()
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options. @param data set of instances serving as training data @throws Exception if the clusterer has not been generated successfully
weka.clusterers.FarthestFirst.buildClusterer()
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options. @param data set of instances serving as training data @throws Exception if the clusterer has not been generated successfully
weka.clusterers.HierarchicalClusterer.buildClusterer()
weka.clusterers.SimpleKMeans.buildClusterer()
Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via options. @param data set of instances serving as training data @throws Exception if the clusterer has not been generated successfully

Examples of weka.clusterers.AbstractClusterer.buildClusterer()

        FilteredClusterer filtered_clusterer = new FilteredClusterer();
        filtered_clusterer.setFilter(filter);
        filtered_clusterer.setClusterer(inner_clusterer);
        
        AbstractClusterer clusterer = filtered_clusterer;
        clusterer.buildClusterer(trainingData);
        
        return (clusterer);
    }
    
    protected Classifier generateDecisionTree(AbstractClusterer clusterer, MarkovAttributeSet aset, Instances data) throws Exception {

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Examples of weka.clusterers.EM.buildClusterer()

    options[0] = "-I";
    options[1] = String.valueOf(numberOfIterations);


    try {
      clusterer.setOptions(options);
      clusterer.buildClusterer(dataset);
      Enumeration e = dataset.enumerateInstances();
      while (e.hasMoreElements()) {
        clusters.add(clusterer.clusterInstance((Instance) e
            .nextElement()));
      }

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Examples of weka.clusterers.FarthestFirst.buildClusterer()

    options[0] = "-N";
    options[1] = String.valueOf(numberOfGroups);


    try {
      clusterer.setOptions(options);
      clusterer.buildClusterer(dataset);
      Enumeration e = dataset.enumerateInstances();
      while (e.hasMoreElements()) {
        clusters.add(clusterer.clusterInstance((Instance) e
            .nextElement()));
      }

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Examples of weka.clusterers.HierarchicalClusterer.buildClusterer()


    options[4] = "-P";
    try {
      clusterer.setOptions(options);
      clusterer.setPrintNewick(true);
      clusterer.buildClusterer(dataset);
      // clusterer.graph() gives only the first cluster and in the case
      // there
      // are more than one cluster the variables in the second cluster are
      // missing.
      // I'm using clusterer.toString() which contains all the clusters in

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Examples of weka.clusterers.SimpleKMeans.buildClusterer()

    options[0] = "-N";
    options[1] = String.valueOf(numberOfGroups);


    try {
      clusterer.setOptions(options);
      clusterer.buildClusterer(dataset);
      Enumeration e = dataset.enumerateInstances();
      while (e.hasMoreElements()) {
        clusters.add(clusterer.clusterInstance((Instance) e
            .nextElement()));
      }

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