Examples of OnePassRealValueDataIndexer

Examples of opennlp.model.OnePassRealValueDataIndexer

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  @Test
  public void testInitialSanity() 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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(testDataIndexer);
    // when
    double[] initial = objectFunction.getInitialPoint();
    // then
    for (int i = 0; i < initial.length; i++) {
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Examples of opennlp.model.OnePassRealValueDataIndexer

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  @Test
  public void testGradientSanity() 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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(testDataIndexer);
    // when
    double[] initial = objectFunction.getInitialPoint();
    double[] gradientAtInitial = objectFunction.gradientAt(initial);
    // then
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Examples of opennlp.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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(testDataIndexer);
    // when
    double value = objectFunction.valueAt(objectFunction.getInitialPoint());
    double expectedValue = -13.86294361;
    // then
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Examples of opennlp.model.OnePassRealValueDataIndexer

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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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(testDataIndexer);
    // when
    double[] nonInitialPoint = new double[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
    double value = objectFunction.valueAt(nonInitialPoint);
    double expectedValue = -0.000206886;
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Examples of opennlp.model.OnePassRealValueDataIndexer

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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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(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 = -0.00000000285417;
    // then
    assertEquals(expectedValue, value, TOLERANCE02);
  }
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Examples of opennlp.model.OnePassRealValueDataIndexer

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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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(testDataIndexer);
    // when
    double[] gradientAtInitialPoint = objectFunction.gradientAt(objectFunction.getInitialPoint());
    double[] expectedGradient = new double[] { -9, -14, -17, 20, 8.5, 9, 14, 17, -20, -8.5 };
    // then
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Examples of opennlp.model.OnePassRealValueDataIndexer

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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);
    LogLikelihoodFunction objectFunction = new LogLikelihoodFunction(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[] { -0.311616214, -0.211771052, -1.324041847, 0.93340278, 0.317407069,
        0.311616214, 0.211771052, 1.324041847, -0.93340278, -0.317407069 };  
    // then
    assertTrue(compareDoubleArray(expectedGradient, gradientAtNonInitialPoint, testDataIndexer, TOLERANCE01));
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Examples of opennlp.model.OnePassRealValueDataIndexer

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public class QNTrainerTest {
  @Test
  public void testTrainModelReturnsAQNModel() throws Exception {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream("src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt"); 
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    // when
    QNModel trainedModel = new QNTrainer(false).trainModel(testDataIndexer);
    // then
    assertNotNull(trainedModel);
  }
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Examples of opennlp.model.OnePassRealValueDataIndexer

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  @Test
  public void testInTinyDevSet() throws Exception {
    // given
    RealValueFileEventStream rvfes1 = new RealValueFileEventStream("src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt"); 
    DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
    // when
    QNModel trainedModel = new QNTrainer(15, true).trainModel(testDataIndexer);
    String[] features2Classify = new String[] {"feature2","feature3", "feature3", "feature3","feature3", "feature3", "feature3","feature3", "feature3", "feature3","feature3", "feature3"};
    double[] eval = trainedModel.eval(features2Classify);
    // then
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Examples of opennlp.model.OnePassRealValueDataIndexer

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  @Test
  public void testModel() throws IOException {
      // given
      RealValueFileEventStream rvfes1 = new RealValueFileEventStream("src/test/resources/data/opennlp/maxent/real-valued-weights-training-data.txt"); 
      DataIndexer testDataIndexer = new OnePassRealValueDataIndexer(rvfes1,1);
      // when
      QNModel trainedModel = new QNTrainer(15, true).trainModel(testDataIndexer);
     
      assertTrue(trainedModel.equals(trainedModel)); 
      assertFalse(trainedModel.equals(null));
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