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

Example 11 with Attribute

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

the class AdaBoostTest method testUSPSNominal.

/**
     * Test of learn method, of class AdaBoost.
     */
@Test
public void testUSPSNominal() {
    System.out.println("USPS nominal");
    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()]);
        for (double[] xi : x) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(255 * (xi[i] + 1) / 2);
            }
        }
        for (double[] xi : testx) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(255 * (xi[i] + 1) / 2);
            }
        }
        Attribute[] attributes = new Attribute[256];
        String[] values = new String[attributes.length];
        for (int i = 0; i < attributes.length; i++) {
            values[i] = String.valueOf(i);
        }
        for (int i = 0; i < attributes.length; i++) {
            attributes[i] = new NominalAttribute("V" + i, values);
        }
        for (int i = 0; i < y.length; i++) {
            if (y[i] != 0)
                y[i] = 1;
        }
        for (int i = 0; i < testy.length; i++) {
            if (testy[i] != 0)
                testy[i] = 1;
        }
        AdaBoost forest = new AdaBoost(attributes, x, y, 100, 6);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (forest.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.println("AdaBoost error = " + error);
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        assertTrue(error <= 25);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 12 with Attribute

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

the class DateFeatureTest method testAttributes.

/**
     * Test of attributes method, of class DateFeature.
     */
@Test
public void testAttributes() {
    System.out.println("attributes");
    try {
        ArffParser parser = new ArffParser();
        AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/date.arff"));
        DateFeature.Type[] features = { DateFeature.Type.YEAR, DateFeature.Type.MONTH, DateFeature.Type.DAY_OF_MONTH, DateFeature.Type.DAY_OF_WEEK, DateFeature.Type.HOURS, DateFeature.Type.MINUTES, DateFeature.Type.SECONDS };
        DateFeature df = new DateFeature(data.attributes(), features);
        Attribute[] attributes = df.attributes();
        assertEquals(features.length, attributes.length);
        for (int i = 0; i < attributes.length; i++) {
            System.out.println(attributes[i]);
            assertEquals(Attribute.Type.NUMERIC, attributes[i].getType());
        }
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 13 with Attribute

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

the class FeatureSetTest method testF.

/**
     * Test of f method, of class FeatureSet.
     */
@Test
public void testF() {
    System.out.println("f");
    try {
        ArffParser parser = new ArffParser();
        AttributeDataset data = parser.parse(smile.data.parser.IOUtils.getTestDataFile("weka/regression/abalone.arff"));
        double[][] x = data.toArray(new double[data.size()][]);
        FeatureSet<double[]> features = new FeatureSet<>();
        features.add(new Nominal2Binary(data.attributes()));
        features.add(new NumericAttributeFeature(data.attributes(), 0.05, 0.95, x));
        AttributeDataset dataset = features.f(data);
        assertEquals(data.size(), dataset.size());
        assertEquals(data.getName(), dataset.getName());
        assertEquals(data.getDescription(), dataset.getDescription());
        Attribute[] attributes = features.attributes();
        for (int i = 0; i < attributes.length; i++) {
            assertEquals(attributes[i].getName(), dataset.attributes()[i].getName());
            assertEquals(attributes[i].getType(), dataset.attributes()[i].getType());
        }
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 14 with Attribute

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

the class RandomForestTest method testUSPSNominal.

/**
     * Test of learn method, of class RandomForest.
     */
@Test
public void testUSPSNominal() {
    System.out.println("USPS nominal");
    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()]);
        for (double[] xi : x) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(255 * (xi[i] + 1) / 2);
            }
        }
        for (double[] xi : testx) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(255 * (xi[i] + 1) / 2);
            }
        }
        Attribute[] attributes = new Attribute[256];
        String[] values = new String[attributes.length];
        for (int i = 0; i < attributes.length; i++) {
            values[i] = String.valueOf(i);
        }
        for (int i = 0; i < attributes.length; i++) {
            attributes[i] = new NominalAttribute("V" + i, values);
        }
        RandomForest forest = new RandomForest(attributes, 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);
        double[] accuracy = forest.test(testx, testy);
        for (int i = 1; i <= accuracy.length; i++) {
            System.out.format("%d trees accuracy = %.2f%%%n", i, 100.0 * accuracy[i - 1]);
        }
        double[] importance = forest.importance();
        int[] index = QuickSort.sort(importance);
        for (int i = importance.length; i-- > 0; ) {
            System.out.format("%s importance is %.4f%n", train.attributes()[index[i]], importance[i]);
        }
        assertTrue(error <= 150);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}

Example 15 with Attribute

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

the class DecisionTreeTest method testUSPSNominal.

/**
     * Test of learn method, of class DecisionTree.
     */
@Test
public void testUSPSNominal() {
    System.out.println("USPS nominal");
    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()]);
        for (double[] xi : x) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(255 * (xi[i] + 1) / 2);
            }
        }
        for (double[] xi : testx) {
            for (int i = 0; i < xi.length; i++) {
                xi[i] = Math.round(127 + 127 * xi[i]);
            }
        }
        Attribute[] attributes = new Attribute[256];
        String[] values = new String[attributes.length];
        for (int i = 0; i < attributes.length; i++) {
            values[i] = String.valueOf(i);
        }
        for (int i = 0; i < attributes.length; i++) {
            attributes[i] = new NominalAttribute("V" + i, values);
        }
        DecisionTree tree = new DecisionTree(attributes, x, y, 350, 2, DecisionTree.SplitRule.ENTROPY);
        int error = 0;
        for (int i = 0; i < testx.length; i++) {
            if (tree.predict(testx[i]) != testy[i]) {
                error++;
            }
        }
        System.out.format("USPS error rate = %.2f%%%n", 100.0 * error / testx.length);
        double[] importance = tree.importance();
        int[] index = QuickSort.sort(importance);
        for (int i = importance.length; i-- > 0; ) {
            System.out.format("%s importance is %.4f%n", train.attributes()[index[i]], importance[i]);
        }
        assertEquals(324, error);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}