Examples with AttributeDataset smile.data.AttributeDataset used on opensource projects

Example 6 with AttributeDataset

use of smile.data.AttributeDataset 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 7 with AttributeDataset

use of smile.data.AttributeDataset 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);
    }
}

Example 8 with AttributeDataset

use of smile.data.AttributeDataset in project smile by haifengl.

the class ValidationTest method testLoocv_3args_2.

/**
     * Test of loocv method, of class Validation.
     */
@Test
public void testLoocv_3args_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);
        double rmse = Validation.loocv(trainer, x, y);
        System.out.println("RMSE = " + rmse);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 9 with AttributeDataset

use of smile.data.AttributeDataset in project smile by haifengl.

the class ValidationTest method testLoocv_3args_1.

/**
     * Test of loocv method, of class Validation.
     */
@Test
public void testLoocv_3args_1() {
    System.out.println("loocv");
    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.loocv(trainer, x, y);
        System.out.println("LOOCV accuracy = " + accuracy);
        assertEquals(0.8533, accuracy, 1E-4);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 10 with AttributeDataset

use of smile.data.AttributeDataset in project smile by haifengl.

the class ValidationTest method testCv_5args_2.

/**
     * Test of cv method, of class Validation.
     */
@Test
public void testCv_5args_2() {
    System.out.println("cv");
    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.cv(10, trainer, x, y, measures);
        System.out.println("RMSE = " + results[0]);
        System.out.println("Absolute Deviation = " + results[1]);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}