Examples with SVM smile.classification.SVM used on opensource projects

Example 1 with SVM

use of smile.classification.SVM in project smile by haifengl.

the class SVMDemo method learn.

@Override
public double[][] learn(double[] x, double[] y) {
    try {
        gamma = Double.parseDouble(gammaField.getText().trim());
        if (gamma <= 0) {
            JOptionPane.showMessageDialog(this, "Invalid ˠ: " + gamma, "Error", JOptionPane.ERROR_MESSAGE);
            return null;
        }
    } catch (Exception ex) {
        JOptionPane.showMessageDialog(this, "Invalid ˠ: " + gammaField.getText(), "Error", JOptionPane.ERROR_MESSAGE);
        return null;
    }
    try {
        C = Double.parseDouble(cField.getText().trim());
        if (C < 0) {
            JOptionPane.showMessageDialog(this, "Invalid C: " + C, "Error", JOptionPane.ERROR_MESSAGE);
            return null;
        }
    } catch (Exception ex) {
        JOptionPane.showMessageDialog(this, "Invalid C: " + cField.getText(), "Error", JOptionPane.ERROR_MESSAGE);
        return null;
    }
    double[][] data = dataset[datasetIndex].toArray(new double[dataset[datasetIndex].size()][]);
    int[] label = dataset[datasetIndex].toArray(new int[dataset[datasetIndex].size()]);
    SVM<double[]> svm = new SVM<>(new GaussianKernel(gamma), C);
    svm.learn(data, label);
    svm.finish();
    for (int i = 0; i < label.length; i++) {
        label[i] = svm.predict(data[i]);
    }
    double trainError = error(label, label);
    System.out.format("training error = %.2f%%\n", 100 * trainError);
    double[][] z = new double[y.length][x.length];
    for (int i = 0; i < y.length; i++) {
        for (int j = 0; j < x.length; j++) {
            double[] p = { x[j], y[i] };
            z[i][j] = svm.predict(p);
        }
    }
    return z;
}