Examples of RejectionSampling

aima.core.probability.bayes.approx.RejectionSampling

Artificial Intelligence A Modern Approach (3rd Edition): page 533.

 function REJECTION-SAMPLING(X, e, bn, N) returns an estimate of P(X|e) inputs: X, the query variable e, observed values for variables E bn, a Bayesian network N, the total number of samples to be generated local variables: N, a vector of counts for each value of X, initially zero for j = 1 to N do x <- PRIOR-SAMPLE(bn) if x is consistent with e then N[x] <- N[x] + 1 where x is the value of X in x return NORMALIZE(N)

Figure 14.14 The rejection-sampling algorithm for answering queries given evidence in a Bayesian Network.

Note: The implementation has been extended to handle queries with multiple variables.
@author Ciaran O'Reilly @author Ravi Mohan

Examples of aima.core.probability.bayes.approx.RejectionSampling

  public static void bayesRejectionSamplingDemo() {
    System.out.println("DEMO: Bayes Rejection Sampling N = " + NUM_SAMPLES);
    System.out.println("==============================");
    demoToothacheCavityCatchModel(new FiniteBayesModel(
        BayesNetExampleFactory.constructToothacheCavityCatchNetwork(),
        new BayesInferenceApproxAdapter(new RejectionSampling(),
            NUM_SAMPLES)));
    demoBurglaryAlarmModel(new FiniteBayesModel(
        BayesNetExampleFactory.constructBurglaryAlarmNetwork(),
        new BayesInferenceApproxAdapter(new RejectionSampling(),
            NUM_SAMPLES)));
    System.out.println("==============================");
  }

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Examples of aima.core.probability.bayes.approx.RejectionSampling

    BayesianNetwork bn = BayesNetExampleFactory
        .constructCloudySprinklerRainWetGrassNetwork();
    AssignmentProposition[] e = new AssignmentProposition[] { new AssignmentProposition(
        ExampleRV.SPRINKLER_RV, Boolean.TRUE) };
    MockRandomizer r = new MockRandomizer(new double[] { 0.1 });
    RejectionSampling rs = new RejectionSampling(new PriorSample(r));


    double[] estimate = rs.rejectionSampling(
        new RandomVariable[] { ExampleRV.RAIN_RV }, e, bn, 100)
        .getValues();


    Assert.assertArrayEquals(new double[] { 1.0, 0.0 }, estimate,
        DELTA_THRESHOLD);

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Examples of aima.core.probability.bayes.approx.RejectionSampling


        ma[i + 3] = 0.1; // i.e. WetGrass=true
      }
    }
    MockRandomizer r = new MockRandomizer(ma);
    RejectionSampling rs = new RejectionSampling(new PriorSample(r));


    double[] estimate = rs.rejectionSampling(
        new RandomVariable[] { ExampleRV.RAIN_RV }, e, bn, 100)
        .getValues();


    Assert.assertArrayEquals(new double[] { 0.2962962962962963,
        0.7037037037037037 }, estimate, DELTA_THRESHOLD);

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