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

Example 61 with ArffParser

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

the class LDATest method testLearn.

/**
     * Test of learn method, of class LDA.
     */
@Test
public void testLearn() {
    System.out.println("learn");
    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()]);
        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        int error = 0;
        double[] posteriori = new double[3];
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);
            LDA lda = new LDA(trainx, trainy);
            if (y[loocv.test[i]] != lda.predict(x[loocv.test[i]], posteriori))
                error++;
        //System.out.println(posteriori[0]+"\t"+posteriori[1]+"\t"+posteriori[2]);
        }
        System.out.println("LDA error = " + error);
        assertEquals(22, error);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 62 with ArffParser

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

the class RBFNetworkTest method testLearn.

/**
     * Test of learn method, of class RBFNetwork.
     */
@Test
public void testLearn() {
    System.out.println("learn");
    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()]);
        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]);
            double[][] centers = new double[10][];
            RadialBasisFunction[] basis = SmileUtils.learnGaussianRadialBasis(trainx, centers, 5.0);
            RBFNetwork<double[]> rbf = new RBFNetwork<>(trainx, trainy, new EuclideanDistance(), basis, centers);
            if (y[loocv.test[i]] != rbf.predict(x[loocv.test[i]]))
                error++;
        }
        System.out.println("RBF network error = " + error);
        assertTrue(error <= 6);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 63 with ArffParser

use of smile.data.parser.ArffParser 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 64 with ArffParser

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

the class SVMTest method testSegment.

/**
     * Test of learn method, of class SVM.
     */
@Test
public void testSegment() {
    System.out.println("Segment");
    ArffParser parser = new ArffParser();
    parser.setResponseIndex(19);
    try {
        AttributeDataset train = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/segment-challenge.arff"));
        AttributeDataset test = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/segment-test.arff"));
        System.out.println(train.size() + " " + test.size());
        double[][] x = train.toArray(new double[0][]);
        int[] y = train.toArray(new int[0]);
        double[][] testx = test.toArray(new double[0][]);
        int[] testy = test.toArray(new int[0]);
        SVM<double[]> svm = new SVM<>(new GaussianKernel(8.0), 5.0, Math.max(y) + 1, SVM.Multiclass.ONE_VS_ALL);
        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("Segment error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error < 70);
    } catch (Exception ex) {
        ex.printStackTrace();
    }
}

Example 65 with ArffParser

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

the class AdaBoostTest method testWeather.

/**
     * Test of learn method, of class AdaBoost.
     */
@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]);
            AdaBoost forest = new AdaBoost(weather.attributes(), trainx, trainy, 200, 4);
            if (y[loocv.test[i]] != forest.predict(x[loocv.test[i]]))
                error++;
        }
        System.out.println("AdaBoost error = " + error);
        assertEquals(3, error);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}