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

Example 81 with AttributeDataset

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

the class RBFNetworkTest method testUSPS.

/**
     * Test of learn method, of class RBFNetwork.
     */
@Test
public void testUSPS() {
    System.out.println("USPS");
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        double[][] testx = test.toArray(new double[test.size()][]);
        int[] testy = test.toArray(new int[test.size()]);
        double[][] centers = new double[200][];
        RadialBasisFunction basis = SmileUtils.learnGaussianRadialBasis(x, centers);
        RBFNetwork<double[]> rbf = new RBFNetwork<>(x, y, new EuclideanDistance(), new GaussianRadialBasis(8.0), centers);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (rbf.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error <= 150);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 82 with AttributeDataset

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

the class RDATest method testUSPS.

/**
     * Test of learn method, of class RDA.
     */
@Test
public void testUSPS() {
    System.out.println("USPS");
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        double[][] testx = test.toArray(new double[test.size()][]);
        int[] testy = test.toArray(new int[test.size()]);
        RDA rda = new RDA(x, y, 0.7);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (rda.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertEquals(235, error);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 83 with AttributeDataset

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

the class RandomForestTest method testWeather.

/**
     * Test of learn method, of class RandomForest.
     */
@Test
public void testWeather() {
    System.out.println("Weather");
    ArffParser arffParser = new ArffParser();
    arffParser.setResponseIndex(4);
    try {
        AttributeDataset weather = arffParser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/weather.nominal.arff"));
        double[][] x = weather.toArray(new double[weather.size()][]);
        int[] y = weather.toArray(new int[weather.size()]);
        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        int error = 0;
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);
            RandomForest forest = new RandomForest(weather.attributes(), trainx, trainy, 100);
            if (y[loocv.test[i]] != forest.predict(x[loocv.test[i]]))
                error++;
        }
        System.out.println("Random Forest error = " + error);
        assertTrue(error <= 7);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 84 with AttributeDataset

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

the class RandomForestTest method testUSPS.

/**
     * Test of learn method, of class RandomForest.
     */
@Test
public void testUSPS() {
    System.out.println("USPS");
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        double[][] testx = test.toArray(new double[test.size()][]);
        int[] testy = test.toArray(new int[test.size()]);
        RandomForest forest = new RandomForest(x, y, 200);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (forest.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.println(error);
        System.out.format("USPS OOB error rate = %.2f%%%n", 100.0 * forest.error());
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error <= 140);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 85 with AttributeDataset

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

the class SVMTest method testUSPS.

/**
     * Test of learn method, of class SVM.
     */
@Test
public void testUSPS() {
    System.out.println("USPS");
    DelimitedTextParser parser = new DelimitedTextParser();
    parser.setResponseIndex(new NominalAttribute("class"), 0);
    try {
        AttributeDataset train = parser.parse("USPS Train", smile.data.parser.IOUtils.getTestDataFile("usps/zip.train"));
        AttributeDataset test = parser.parse("USPS Test", smile.data.parser.IOUtils.getTestDataFile("usps/zip.test"));
        double[][] x = train.toArray(new double[train.size()][]);
        int[] y = train.toArray(new int[train.size()]);
        double[][] testx = test.toArray(new double[test.size()][]);
        int[] testy = test.toArray(new int[test.size()]);
        SVM<double[]> svm = new SVM<>(new GaussianKernel(8.0), 5.0, Math.max(y) + 1, SVM.Multiclass.ONE_VS_ONE);
        svm.learn(x, y);
        svm.finish();
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (svm.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error < 95);
        System.out.println("USPS one more epoch...");
        for (int i = 0; i < x.length; i++) {
            int j = Math.randomInt(x.length);
            svm.learn(x[j], y[j]);
        }
        svm.finish();
        error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (svm.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error < 95);
    } catch (Exception ex) {
        ex.printStackTrace();
    }
}