Package aima.core.learning.learners

Examples of aima.core.learning.learners.DecisionTreeLearner.train()

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        .println("\nDecisionTree Demo - Inducing a DecisionList from the Restaurant DataSet\n ");
    System.out.println(Util.ntimes("*", 100));
    try {
      DataSet ds = DataSetFactory.getRestaurantDataSet();
      DecisionTreeLearner learner = new DecisionTreeLearner();
      learner.train(ds);
      System.out.println("The Induced Decision Tree is ");
      System.out.println(learner.getDecisionTree());
      int[] result = learner.test(ds);

      System.out
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    DecisionTreeLearner learner = new DecisionTreeLearner();

    DataSet ds2 = ds.emptyDataSet();
    Assert.assertEquals(0, ds2.size());

    learner.train(ds2);
    Assert.assertEquals("Unable To Classify",
        learner.predict(ds.getExample(0)));
  }

  @Test
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    // all 3 examples have the same classification (willWait = yes)
    ds2.add(ds.getExample(0));
    ds2.add(ds.getExample(2));
    ds2.add(ds.getExample(3));

    learner.train(ds2);
    Assert.assertEquals("Yes", learner.predict(ds.getExample(0)));
  }

  @Test
  public void testMajorityReturnedWhenAttributesToExamineIsEmpty()
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    ds2.add(ds.getExample(1));// "no"
    ds2.add(ds.getExample(2));
    ds2.add(ds.getExample(3));
    ds2.setSpecification(new MockDataSetSpecification("will_wait"));

    learner.train(ds2);
    Assert.assertEquals("Yes", learner.predict(ds.getExample(1)));
  }

  @Test
  public void testInducedTreeClassifiesDataSetCorrectly() throws Exception {
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  @Test
  public void testInducedTreeClassifiesDataSetCorrectly() throws Exception {
    DataSet ds = DataSetFactory.getRestaurantDataSet();
    DecisionTreeLearner learner = new DecisionTreeLearner();
    learner.train(ds);
    int[] result = learner.test(ds);
    Assert.assertEquals(12, result[0]);
    Assert.assertEquals(0, result[1]);
  }
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