Package com.github.pmerienne.trident.ml.classification

Examples of com.github.pmerienne.trident.ml.classification.MultiClassPAClassifier

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public class MultiClassPATest extends ClassifierTest {

  @Test
  public void testWithGaussianData() {
    List<Instance<Integer>> dataset = Datasets.generateDataForMultiLabelClassification(5000, 10, 10);
    double actualError = this.eval(new MultiClassPAClassifier(10), dataset);
    double actualError1 = this.eval(new MultiClassPAClassifier(10, Type.PA1), dataset);
    double actualError2 = this.eval(new MultiClassPAClassifier(10, Type.PA2), dataset);

    assertTrue("Error " + actualError + " is to big!", actualError < 0.05);
    assertTrue("Error " + actualError1 + " is to big!", actualError1 < 0.05);
    assertTrue("Error " + actualError2 + " is to big!", actualError2 < 0.05);
  }
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    assertTrue("Error " + actualError2 + " is to big!", actualError2 < 0.05);
  }

  @Test
  public void testWithUSPS() {
    double actualError = this.eval(new MultiClassPAClassifier(10), Datasets.getUSPSSamples());
    double actualError1 = this.eval(new MultiClassPAClassifier(10, Type.PA1), Datasets.getUSPSSamples());
    double actualError2 = this.eval(new MultiClassPAClassifier(10, Type.PA2), Datasets.getUSPSSamples());

    assertTrue("Error " + actualError + " is to big!", actualError < 0.30);
    assertTrue("Error " + actualError1 + " is to big!", actualError1 < 0.30);
    assertTrue("Error " + actualError2 + " is to big!", actualError2 < 0.30);
  }
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Related Classes of com.github.pmerienne.trident.ml.classification.MultiClassPAClassifier

  • com.github.pmerienne.trident.ml.classification.MultiClassPATest
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