Examples of aima.core.learning.neural.RabbitEyeDataSet

  DataSetSpecification spec;


  @Test
  public void testNormalizationOfFileBasedDataProducesCorrectMeanStdDevAndNormalizedValues()
      throws Exception {
    RabbitEyeDataSet reds = new RabbitEyeDataSet();
    reds.createNormalizedDataFromFile("rabbiteyes");


    List<Double> means = reds.getMeans();
    Assert.assertEquals(2, means.size());
    Assert.assertEquals(244.771, means.get(0), 0.001);
    Assert.assertEquals(145.505, means.get(1), 0.001);


    List<Double> stdev = reds.getStdevs();
    Assert.assertEquals(2, stdev.size());
    Assert.assertEquals(213.554, stdev.get(0), 0.001);
    Assert.assertEquals(65.776, stdev.get(1), 0.001);


    List<List<Double>> normalized = reds.getNormalizedData();
    Assert.assertEquals(70, normalized.size());


    // check first value
    Assert.assertEquals(-1.0759, normalized.get(0).get(0), 0.001);
    Assert.assertEquals(-1.882, normalized.get(0).get(1), 0.001);

    Assert.assertEquals(1.538, normalized.get(69).get(1), 0.001);
  }


  @Test
  public void testExampleFormation() throws Exception {
    RabbitEyeDataSet reds = new RabbitEyeDataSet();
    reds.createExamplesFromFile("rabbiteyes");
    Assert.assertEquals(70, reds.howManyExamplesLeft());
    reds.getExampleAtRandom();
    Assert.assertEquals(69, reds.howManyExamplesLeft());
    reds.getExampleAtRandom();
    Assert.assertEquals(68, reds.howManyExamplesLeft());
  }

Examples of aima.core.learning.neural.RabbitEyeDataSet

Related Classes of aima.core.learning.neural.RabbitEyeDataSet