Package aima.core.probability

Examples of aima.core.probability.CategoricalDistribution

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    AssignmentProposition astiffNeck = new AssignmentProposition(
        ExampleRV.STIFF_NECK_RV, true);

    // AIMA3e pg. 497
    // P<>(Mengingitis | stiffneck) = &alpha;<P(s | m)P(m), P(s | ~m)P(~m)>
    CategoricalDistribution dMeningitisGivenStiffNeck = model
        .posteriorDistribution(ExampleRV.MENINGITIS_RV, astiffNeck);
    Assert.assertEquals(2, dMeningitisGivenStiffNeck.getValues().length);
    Assert.assertEquals(0.0014, dMeningitisGivenStiffNeck.getValues()[0],
        DELTA_THRESHOLD);
    Assert.assertEquals(0.9986, dMeningitisGivenStiffNeck.getValues()[1],
        DELTA_THRESHOLD);
  }
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  @Test
  public void testInferenceOnToothacheCavityCatchNetwork() {
    BayesianNetwork bn = BayesNetExampleFactory
        .constructToothacheCavityCatchNetwork();

    CategoricalDistribution d = bayesInference.ask(
        new RandomVariable[] { ExampleRV.CAVITY_RV },
        new AssignmentProposition[] {}, bn);

    // System.out.println("P(Cavity)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.2, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.8, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);

    // AIMA3e pg. 493
    // P(Cavity | toothache) = <0.6, 0.4>
    d = bayesInference.ask(new RandomVariable[] { ExampleRV.CAVITY_RV },
        new AssignmentProposition[] { new AssignmentProposition(
            ExampleRV.TOOTHACHE_RV, true) }, bn);

    // System.out.println("P(Cavity | toothache)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.6, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.4, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);

    // AIMA3e pg. 497
    // P(Cavity | toothache AND catch) = <0.871, 0.129>
    d = bayesInference
        .ask(new RandomVariable[] { ExampleRV.CAVITY_RV },
            new AssignmentProposition[] {
                new AssignmentProposition(
                    ExampleRV.TOOTHACHE_RV, true),
                new AssignmentProposition(ExampleRV.CATCH_RV,
                    true) }, bn);

    // System.out.println("P(Cavity | toothache, catch)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.8709677419354839, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.12903225806451615, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
  }
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  public void testInferenceOnBurglaryAlarmNetwork() {
    BayesianNetwork bn = BayesNetExampleFactory
        .constructBurglaryAlarmNetwork();

    // AIMA3e. pg. 514
    CategoricalDistribution d = bayesInference
        .ask(new RandomVariable[] { ExampleRV.ALARM_RV },
            new AssignmentProposition[] {
                new AssignmentProposition(
                    ExampleRV.BURGLARY_RV, false),
                new AssignmentProposition(
                    ExampleRV.EARTHQUAKE_RV, false),
                new AssignmentProposition(
                    ExampleRV.JOHN_CALLS_RV, true),
                new AssignmentProposition(
                    ExampleRV.MARY_CALLS_RV, true) }, bn);

    // System.out.println("P(Alarm | ~b, ~e, j, m)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.5577689243027888, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.44223107569721115, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);

    // AIMA3e pg. 523
    // P(Burglary | JohnCalls = true, MaryCalls = true) = <0.284, 0.716>
    d = bayesInference
        .ask(new RandomVariable[] { ExampleRV.BURGLARY_RV },
            new AssignmentProposition[] {
                new AssignmentProposition(
                    ExampleRV.JOHN_CALLS_RV, true),
                new AssignmentProposition(
                    ExampleRV.MARY_CALLS_RV, true) }, bn);

    // System.out.println("P(Burglary | j, m)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.2841718353643929, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.7158281646356071, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);

    // AIMA3e pg. 528
    // P(JohnCalls | Burglary = true)
    d = bayesInference.ask(
        new RandomVariable[] { ExampleRV.JOHN_CALLS_RV },
        new AssignmentProposition[] { new AssignmentProposition(
            ExampleRV.BURGLARY_RV, true) }, bn);
    // System.out.println("P(JohnCalls | b)=" + d);
    Assert.assertEquals(2, d.getValues().length);
    Assert.assertEquals(0.8490169999999999, d.getValues()[0],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
    Assert.assertEquals(0.15098299999999998, d.getValues()[1],
        ProbabilityModel.DEFAULT_ROUNDING_THRESHOLD);
  }
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Related Classes of aima.core.probability.CategoricalDistribution

  • aima.core.probability.bayes.model.FiniteBayesModel
  • aima.core.probability.full.FullJointDistributionModel
  • aima.core.probability.hmm.exact.FixedLagSmoothing
  • aima.core.probability.temporal.generic.ForwardBackward
  • aima.test.core.unit.probability.bayes.exact.BayesianInferenceTest
  • aima.test.core.unit.probability.CommonFiniteProbabilityModelTests
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