Examples with ArffParser smile.data.parser.ArffParser used on opensource projects

Example 1 with ArffParser

use of smile.data.parser.ArffParser in project smile by haifengl.

the class ValidationTest method testCv_5args_1.

/**
     * Test of cv method, of class Validation.
     */
@Test
public void testCv_5args_1() {
    System.out.println("cv");
    ArffParser arffParser = new ArffParser();
    arffParser.setResponseIndex(4);
    try {
        AttributeDataset iris = arffParser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/iris.arff"));
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);
        ClassifierTrainer<double[]> trainer = new LDA.Trainer();
        ClassificationMeasure[] measures = { new Accuracy() };
        double[] results = Validation.cv(10, trainer, x, y, measures);
        for (int i = 0; i < measures.length; i++) {
            System.out.println(measures[i] + " = " + results[i]);
        }
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 2 with ArffParser

use of smile.data.parser.ArffParser in project smile by haifengl.

the class ValidationTest method testCv_4args_1.

/**
     * Test of cv method, of class Validation.
     */
@Test
public void testCv_4args_1() {
    System.out.println("cv");
    ArffParser arffParser = new ArffParser();
    arffParser.setResponseIndex(4);
    try {
        AttributeDataset iris = arffParser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/iris.arff"));
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);
        ClassifierTrainer<double[]> trainer = new LDA.Trainer();
        double accuracy = Validation.cv(10, trainer, x, y);
        System.out.println("10-fold CV accuracy = " + accuracy);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 3 with ArffParser

use of smile.data.parser.ArffParser in project smile by haifengl.

the class ValidationTest method testTest_4args_2.

/**
     * Test of test method, of class Validation.
     */
@Test
public void testTest_4args_2() {
    System.out.println("test");
    ArffParser parser = new ArffParser();
    parser.setResponseIndex(6);
    try {
        AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/cpu.arff"));
        double[] datay = data.toArray(new double[data.size()]);
        double[][] datax = data.toArray(new double[data.size()][]);
        Math.standardize(datax);
        int n = datax.length;
        int m = 3 * n / 4;
        double[][] x = new double[m][];
        double[] y = new double[m];
        double[][] testx = new double[n - m][];
        double[] testy = new double[n - m];
        int[] index = Math.permutate(n);
        for (int i = 0; i < m; i++) {
            x[i] = datax[index[i]];
            y[i] = datay[index[i]];
        }
        for (int i = m; i < n; i++) {
            testx[i - m] = datax[index[i]];
            testy[i - m] = datay[index[i]];
        }
        double[][] centers = new double[20][];
        RadialBasisFunction[] rbf = SmileUtils.learnGaussianRadialBasis(x, centers, 2);
        RBFNetwork<double[]> rkhs = new RBFNetwork<>(x, y, new EuclideanDistance(), rbf, centers);
        RegressionMeasure[] measures = { new RMSE(), new AbsoluteDeviation() };
        double[] results = Validation.test(rkhs, testx, testy, measures);
        System.out.println("RMSE = " + results[0]);
        System.out.println("Absolute Deviation = " + results[1]);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 4 with ArffParser

use of smile.data.parser.ArffParser in project smile by haifengl.

the class ValidationTest method testLoocv_4args_2.

/**
     * Test of loocv method, of class Validation.
     */
@Test
public void testLoocv_4args_2() {
    System.out.println("loocv");
    ArffParser parser = new ArffParser();
    parser.setResponseIndex(6);
    try {
        AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/cpu.arff"));
        double[] y = data.toArray(new double[data.size()]);
        double[][] x = data.toArray(new double[data.size()][]);
        Math.standardize(x);
        RBFNetwork.Trainer<double[]> trainer = new RBFNetwork.Trainer<>(new EuclideanDistance());
        trainer.setNumCenters(20);
        RegressionMeasure[] measures = { new RMSE(), new AbsoluteDeviation() };
        double[] results = Validation.loocv(trainer, x, y, measures);
        System.out.println("RMSE = " + results[0]);
        System.out.println("Absolute Deviation = " + results[1]);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 5 with ArffParser

use of smile.data.parser.ArffParser in project smile by haifengl.

the class ValidationTest method testBootstrap_4args_1.

/**
     * Test of bootstrap method, of class Validation.
     */
@Test
public void testBootstrap_4args_1() {
    System.out.println("bootstrap");
    ArffParser arffParser = new ArffParser();
    arffParser.setResponseIndex(4);
    try {
        AttributeDataset iris = arffParser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/iris.arff"));
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);
        ClassifierTrainer<double[]> trainer = new LDA.Trainer();
        double[] accuracy = Validation.bootstrap(100, trainer, x, y);
        System.out.println("100-fold bootstrap accuracy average = " + Math.mean(accuracy));
        System.out.println("100-fold bootstrap accuracy std.dev = " + Math.sd(accuracy));
    } catch (Exception ex) {
        System.err.println(ex);
    }
}