Examples with Distribution smile.stat.distribution.Distribution used on opensource projects

Example 1 with Distribution

use of smile.stat.distribution.Distribution in project smile by haifengl.

the class NaiveBayesTest method testPredict.

/**
     * Test of predict method, of class NaiveBayes.
     */
@Test
public void testPredict() {
    System.out.println("predict");
    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 l = 0; l < n; l++) {
            double[][] trainx = Math.slice(x, loocv.train[l]);
            int[] trainy = Math.slice(y, loocv.train[l]);
            int p = trainx[0].length;
            int k = Math.max(trainy) + 1;
            double[] priori = new double[k];
            Distribution[][] condprob = new Distribution[k][p];
            for (int i = 0; i < k; i++) {
                priori[i] = 1.0 / k;
                for (int j = 0; j < p; j++) {
                    ArrayList<Double> axi = new ArrayList<>();
                    for (int m = 0; m < trainx.length; m++) {
                        if (trainy[m] == i) {
                            axi.add(trainx[m][j]);
                        }
                    }
                    double[] xi = new double[axi.size()];
                    for (int m = 0; m < xi.length; m++) {
                        xi[m] = axi.get(m);
                    }
                    condprob[i][j] = new GaussianMixture(xi, 3);
                }
            }
            NaiveBayes bayes = new NaiveBayes(priori, condprob);
            if (y[loocv.test[l]] != bayes.predict(x[loocv.test[l]]))
                error++;
        }
        System.out.format("Iris error rate = %.2f%%%n", 100.0 * error / x.length);
        assertEquals(5, error);
    } catch (Exception ex) {
        System.err.println(ex);
    }
}