Package opennlp.tools.ml.model

Examples of opennlp.tools.ml.model.OnePassRealValueDataIndexer

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  @Test
  public void testValueAtInitialPoint() throws IOException {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream(
        "src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt", "UTF-8");
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    NegLogLikelihood objectFunction = new NegLogLikelihood(testDataIndexer);
    // when
    double value = objectFunction.valueAt(objectFunction.getInitialPoint());
    double expectedValue = 13.86294361;
    // then
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  @Test
  public void testValueAtNonInitialPoint01() throws IOException {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream(
        "src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt", "UTF-8");
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    NegLogLikelihood objectFunction = new NegLogLikelihood(testDataIndexer);
    // when
    double[] nonInitialPoint = new double[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
    double value = objectFunction.valueAt(nonInitialPoint);
    double expectedValue = 13.862943611198894;
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  @Test
  public void testValueAtNonInitialPoint02() throws IOException {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream(
        "src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt", "UTF-8");
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    NegLogLikelihood objectFunction = new NegLogLikelihood(testDataIndexer);
    // when
    double[] nonInitialPoint = new double[] { 3, 2, 3, 2, 3, 2, 3, 2, 3, 2 };
    double value = objectFunction.valueAt(dealignDoubleArrayForTestData(nonInitialPoint,
      testDataIndexer.getPredLabels(),
      testDataIndexer.getOutcomeLabels()));
    double expectedValue = 53.163219721099026;
    // then
    assertEquals(expectedValue, value, TOLERANCE02);
  }
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  @Test
  public void testGradientAtInitialPoint() throws IOException {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream(
        "src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt", "UTF-8");
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    NegLogLikelihood objectFunction = new NegLogLikelihood(testDataIndexer);
    // when
    double[] gradientAtInitialPoint = objectFunction.gradientAt(objectFunction.getInitialPoint());
    double[] expectedGradient = new double[] { -9.0, -14.0, -17.0, 20.0, 8.5, 9.0, 14.0, 17.0, -20.0, -8.5 };
    // then
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  @Test
  public void testGradientAtNonInitialPoint() throws IOException {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream(
        "src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt", "UTF-8");
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    NegLogLikelihood objectFunction = new NegLogLikelihood(testDataIndexer);
    // when
    double[] nonInitialPoint = new double[] { 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5, 0.2, 0.5 };
    double[] gradientAtNonInitialPoint =
        objectFunction.gradientAt(dealignDoubleArrayForTestData(nonInitialPoint,
            testDataIndexer.getPredLabels(),
            testDataIndexer.getOutcomeLabels()));
    double[] expectedGradient =
            new double[] { -12.755042847945553, -21.227127506102434,
                           -72.57790706276435,   38.03525795198456,
                            15.348650889354925,  12.755042847945557,
                            21.22712750610244,   72.57790706276438,
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Related Classes of opennlp.tools.ml.model.OnePassRealValueDataIndexer

  • opennlp.tools.ml.maxent.io.RealValueFileEventStreamTest
  • opennlp.tools.ml.maxent.quasinewton.NegLogLikelihoodTest
  • opennlp.tools.ml.maxent.quasinewton.QNTrainerTest
  • opennlp.tools.ml.maxent.RealValueModelTest
  • opennlp.tools.ml.maxent.ScaleDoesntMatterTest
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