Example usage for weka.classifiers.trees M5P setMinNumInstances

Introduction

In this page you can find the example usage for weka.classifiers.trees M5P setMinNumInstances.

Prototype

public void setMinNumInstances(double minNum) 

Source Link

Document

Set the minimum number of instances to allow at a leaf node

Usage

From source file:lu.lippmann.cdb.dt.ModelTreeFactory.java

License:Open Source License

/**
 * Main method.//w w w  .j  a v  a 2 s  .  co m
 * @param args command line arguments
 */
public static void main(final String[] args) {
    try {
        //final String f="./samples/csv/uci/winequality-red-simplified.csv";
        final String f = "./samples/csv/uci/winequality-white.csv";
        //final String f="./samples/arff/UCI/crimepredict.arff";
        final Instances dataSet = WekaDataAccessUtil.loadInstancesFromARFFOrCSVFile(new File(f));
        System.out.println(dataSet.classAttribute().isNumeric());

        final M5P rt = new M5P();
        //rt.setUnpruned(true);
        rt.setMinNumInstances(1000);
        rt.buildClassifier(dataSet);

        System.out.println(rt);

        System.out.println(rt.graph());

        final GraphWithOperations gwo = GraphUtil.buildGraphWithOperationsFromWekaRegressionString(rt.graph());
        System.out.println(gwo);
        System.out.println(new ASCIIGraphDsl().getDslString(gwo));

        final Evaluation eval = new Evaluation(dataSet);

        /*Field privateStringField = Evaluation.class.getDeclaredField("m_CoverageStatisticsAvailable");
        privateStringField.setAccessible(true);
        //privateStringField.get
        boolean fieldValue = privateStringField.getBoolean(eval);
        System.out.println("fieldValue = " + fieldValue);*/

        double[] d = eval.evaluateModel(rt, dataSet);
        System.out.println("PREDICTED -> " + FormatterUtil.buildStringFromArrayOfDoubles(d));

        System.out.println(eval.errorRate());
        System.out.println(eval.sizeOfPredictedRegions());

        System.out.println(eval.toSummaryString("", true));

        System.out.println(new DecisionTree(gwo, eval.errorRate()));
    } catch (Exception e) {
        e.printStackTrace();
    }
}

---