Exemple #1
0
  /** 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);
    }
  }
Exemple #2
0
  /** Test of learn method, of class RDA. */
  @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]);

        RDA rda = new RDA(trainx, trainy, 0.0);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.0) error = " + error);
      assertEquals(22, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.1);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.1) error = " + error);
      assertEquals(24, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.2);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.2) error = " + error);
      assertEquals(20, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.3);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.3) error = " + error);
      assertEquals(19, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.4);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.4) error = " + error);
      assertEquals(16, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.5);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.5) error = " + error);
      assertEquals(12, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.6);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.6) error = " + error);
      assertEquals(11, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.7);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.7) error = " + error);
      assertEquals(9, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.8);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]], posteriori)) error++;

        // System.out.println(posteriori[0]+"\t"+posteriori[1]+"\t"+posteriori[2]);
      }
      System.out.println("RDA (0.8) error = " + error);
      assertEquals(6, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 0.9);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (0.9) error = " + error);
      assertEquals(3, error);

      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]);

        RDA rda = new RDA(trainx, trainy, 1.0);
        if (y[loocv.test[i]] != rda.predict(x[loocv.test[i]])) error++;
      }
      System.out.println("RDA (1.0) error = " + error);
      assertEquals(4, error);
    } catch (Exception ex) {
      System.err.println(ex);
    }
  }