Package org.encog.ml.hmm.distributions

Examples of org.encog.ml.hmm.distributions.DiscreteDistribution

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      new HiddenMarkovModel(2, 2);
   
    hmm.setPi(0, 0.95);
    hmm.setPi(1, 0.05);
   
    hmm.setStateDistribution(0, new DiscreteDistribution(new double[][] { { 0.95, 0.05 } }));
    hmm.setStateDistribution(1, new DiscreteDistribution(new double[][] { { 0.20, 0.80 } }));
   
    hmm.setTransitionProbability(0, 1, 0.05);
    hmm.setTransitionProbability(0, 0, 0.95);
    hmm.setTransitionProbability(1, 0, 0.10);
    hmm.setTransitionProbability(1, 1, 0.90);
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      new HiddenMarkovModel(2, 2);
   
    hmm.setPi(0, 0.95);
    hmm.setPi(1, 0.05);
   
    hmm.setStateDistribution(0, new DiscreteDistribution(new double[][] { { 0.95, 0.05 } }));
    hmm.setStateDistribution(1, new DiscreteDistribution(new double[][] { { 0.20, 0.80 } }));
   
    hmm.setTransitionProbability(0, 1, 0.05);
    hmm.setTransitionProbability(0, 0, 0.95);
    hmm.setTransitionProbability(1, 0, 0.10);
    hmm.setTransitionProbability(1, 1, 0.90);
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    HiddenMarkovModel hmm = new HiddenMarkovModel(2,2);
   
    hmm.setPi(0, 0.50);
    hmm.setPi(1, 0.50);
   
    hmm.setStateDistribution(0, new DiscreteDistribution(new double[][] { { 0.8, 0.2 } }));
    hmm.setStateDistribution(1, new DiscreteDistribution(new double[][] { { 0.1, 0.9 } }));
   
    hmm.setTransitionProbability(0, 1, 0.2);
    hmm.setTransitionProbability(0, 0, 0.8);
    hmm.setTransitionProbability(1, 0, 0.2);
    hmm.setTransitionProbability(1, 1, 0.8);
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    this.transitionProbability = new double[theStates][theStates];
    this.stateDistributions = new StateDistribution[theStates];

    for (int i = 0; i < theStates; i++) {
      this.pi[i] = 1. / theStates;
      this.stateDistributions[i] = new DiscreteDistribution(this.items);

      for (int j = 0; j < theStates; j++) {
        this.transitionProbability[i][j] = 1.0 / theStates;
      }
    }
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  public StateDistribution createNewDistribution() {
    if (isContinuous()) {
      return new ContinousDistribution(getStateCount());
    } else {
      return new DiscreteDistribution(this.items);
    }
  }
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          Matrix cova = section.parseMatrix(params, HiddenMarkovModel.TAG_COVARIANCE);
          ContinousDistribution dist = new ContinousDistribution(mean,cova.getData());
          distributions.add(dist);
        } else if( "DiscreteDistribution".equals(t) ) {
          Matrix prob = section.parseMatrix(params, HiddenMarkovModel.TAG_PROBABILITIES);
          DiscreteDistribution dist = new DiscreteDistribution(prob.getData());
          distributions.add(dist);
        }
      }
    }
   
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        ContinousDistribution cDist = (ContinousDistribution)sd;
        out.writeProperty(HiddenMarkovModel.TAG_MEAN, cDist.getMean());
        out.writeProperty(HiddenMarkovModel.TAG_COVARIANCE, cDist.getCovariance());
       
      } else if( sd instanceof DiscreteDistribution ) {
        DiscreteDistribution dDist = (DiscreteDistribution)sd;
        out.writeProperty(HiddenMarkovModel.TAG_PROBABILITIES, new Matrix(dDist.getProbabilities()));
      }
    }

    out.flush();
  }
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Related Classes of org.encog.ml.hmm.distributions.DiscreteDistribution

  • org.encog.ml.data.basic.BasicMLData
  • org.encog.ml.data.basic.BasicMLDataPair
  • org.encog.ml.data.MLData
  • org.encog.ml.hmm.HiddenMarkovModel
  • org.encog.ml.hmm.PersistHMM
  • org.encog.ml.hmm.TestHMM
  • org.encog.persist.TestPersistHMM
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