Examples of ViterbiCalculator

be.ac.ulg.montefiore.run.jahmm.ViterbiCalculator
This class can be used to compute the most probable state sequence matching a given observation sequence (given an HMM).
org.encog.ml.hmm.alog.ViterbiCalculator
The Viterbi algorithm is used to find the most likely sequence of hidden states (called the Viterbi path) that results in a sequence of observed events. Used for the Markov information sources, and more generally, hidden Markov models (HMM). Viterbi AJ (April 1967). "Error bounds for convolutional codes and an asymptotically optimum decoding algorithm" . IEEE Transactions on Information Theory 13 (2): 260-269. doi:10.1109/TIT.1967.1054010.

Examples of be.ac.ulg.montefiore.run.jahmm.ViterbiCalculator

    int cnt = 0;
    String line;


    while ((line = br.readLine()) != null) {
      ArrayList<ObservationInteger> seq = taxo.obSeqWithBoundarySymbols(line.split(" "));
      double p = (new ViterbiCalculator(seq, this)).lnProbability();
      sumProb += Math.exp(p);
      sumLogProb += p;
      cnt++;
    }
    return sumLogProb;

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Examples of be.ac.ulg.montefiore.run.jahmm.ViterbiCalculator

   * @param seq The sequence to be evaluated
   * @return The log probability of that sequence
   */
  public double viterbiCalculate(ArrayList<String> seq) {
    ArrayList<ObservationInteger> oSeq = taxo.obSeqWithBoundarySymbols(seq);
    ViterbiCalculator vc = new ViterbiCalculator(oSeq, this);
    return vc.lnProbability();
  }

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Examples of be.ac.ulg.montefiore.run.jahmm.ViterbiCalculator

   * 
   * @param seq The sequence of symbols being evaluated
   * @return The most likely sequence of states to produce that sequence
   */
  public State[] viterbiPath(ArrayList<String> seq) {
    ViterbiCalculator vc = new ViterbiCalculator(taxo.obSeqWithBoundarySymbols(seq), this);
    int[] stateSequence = vc.stateSequence();
    State[] ms = new State[stateSequence.length];
    for (int i = 0; i < stateSequence.length; i++) {
      ms[i] = taxo.getState(stateSequence[i]);
    }
    return ms;

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Examples of org.encog.ml.hmm.alog.ViterbiCalculator

    return this.stateDistributions[i];
  }


  @Override
  public int[] getStatesForSequence(final MLDataSet seq) {
    return (new ViterbiCalculator(seq, this)).stateSequence();
  }

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Examples of org.encog.ml.hmm.alog.ViterbiCalculator


  private boolean optimizeCluster(final HiddenMarkovModel hmm) {
    boolean modif = false;


    for (final MLDataSet obsSeq : this.sequnces.getSequences()) {
      final ViterbiCalculator vc = new ViterbiCalculator(obsSeq, hmm);
      final int states[] = vc.stateSequence();


      for (int i = 0; i < states.length; i++) {
        final MLDataPair o = obsSeq.get(i);


        if (this.clusters.cluster(o) != states[i]) {

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