Example usage for weka.classifiers.trees.m5 PreConstructedLinearModel coefficients

Introduction

In this page you can find the example usage for weka.classifiers.trees.m5 PreConstructedLinearModel coefficients.

Prototype

public double[] coefficients() 

Source Link

Document

Return the array of coefficients

Usage

From source file:cn.ict.zyq.bestConf.COMT2.Branch2.java

License:Open Source License

public Instance maxPoint(Instances dataset) throws Exception {
    Instance max = new DenseInstance(dataset.numAttributes());
    max.setDataset(dataset);/*w  ww.java  2 s  . c o  m*/

    double[] combinedCoefs = null;
    int len = 0;
    for (PreConstructedLinearModel model : linearModelList) {
        //initialization
        if (combinedCoefs == null) {
            len = model.coefficients().length;
            combinedCoefs = new double[len];
            for (int i = 0; i < len; i++)
                combinedCoefs[i] = 0;
        }

        for (int i = 0; i < len; i++)
            combinedCoefs[i] += model.coefficients()[i];
    }

    //the max value is obtained at ends of a range
    for (Map.Entry<Attribute, Range<Double>> ent : rangeMap.entrySet()) {
        int attIdx = ent.getKey().index();
        if (combinedCoefs[attIdx] > 0) {
            //use the upper bound
            if (ent.getValue().hasUpperBound())
                max.setValue(attIdx, ent.getValue().upperEndpoint());
        } else if (combinedCoefs[attIdx] < 0) {
            //use the lower bound
            if (ent.getValue().hasLowerBound())
                max.setValue(attIdx, ent.getValue().lowerEndpoint());
        }
    }

    //now we set the predicted values
    double y = 0;
    for (PreConstructedLinearModel model : linearModelList) {
        y += model.classifyInstance(max);
    }
    y /= linearModelList.size();
    max.setClassValue(y);

    return max;
}

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