Examples of JunctionTreeInferencer

Examples of cc.mallet.grmm.inference.JunctionTreeInferencer

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   * Computes the exact entropy of a factor graph distribution using the junction tree algorithm.
   *  If the model is intractable, then this method won't return a number anytime soon.
   */
  public static double entropy (FactorGraph mdl)
  {
    JunctionTreeInferencer inf = new JunctionTreeInferencer ();
    inf.computeMarginals (mdl);
    JunctionTree jt = inf.lookupJunctionTree ();
    return jt.entropy ();
  }
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Examples of cc.mallet.grmm.inference.JunctionTreeInferencer

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   * @param mdl2
   * @return KL(mdl1||mdl2)
   */
  public static double KL (FactorGraph mdl1, FactorGraph mdl2)
  {
    JunctionTreeInferencer inf1 = new JunctionTreeInferencer ();
    inf1.computeMarginals (mdl1);
    JunctionTree jt1 = inf1.lookupJunctionTree ();

    JunctionTreeInferencer inf2 = new JunctionTreeInferencer ();
    inf2.computeMarginals (mdl2);
    JunctionTree jt2 = inf2.lookupJunctionTree ();

    double entropy = jt1.entropy ();
    double energy = 0;

    for (Iterator it = jt2.clusterPotentials ().iterator(); it.hasNext();) {
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Examples of cc.mallet.grmm.inference.JunctionTreeInferencer

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      mdl.addFactor (v1, v2, ptlarr);
    }

    // STEP 2: Compute marginals

    Inferencer inf = new JunctionTreeInferencer ();
    inf.computeMarginals (mdl);

    // STEP 3: Collect the results
    //   We'll just print them out

    for (int varnum = 0; varnum < allVars.length; varnum++) {
      Variable var = allVars[varnum];
      Factor ptl = inf.lookupMarginal (var);
      for (AssignmentIterator it = ptl.assignmentIterator (); it.hasNext (); it.advance()) {
        int outcome = it.indexOfCurrentAssn ();
        System.out.println (var+"  "+outcome+"   "+ptl.value (it));
      }
      System.out.println ();
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Examples of cc.mallet.grmm.inference.JunctionTreeInferencer

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      mdl.addFactor (v1, v2, ptlarr);
    }

    // STEP 2: Compute marginals

    Inferencer inf = new JunctionTreeInferencer ();
    inf.computeMarginals (mdl);

    // STEP 3: Collect the results
    //   We'll just print them out

    for (int varnum = 0; varnum < allVars.length; varnum++) {
      Variable var = allVars[varnum];
      Factor ptl = inf.lookupMarginal (var);
      for (AssignmentIterator it = ptl.assignmentIterator (); it.hasNext ();) {
        int outcome = it.indexOfCurrentAssn ();
        System.out.println (var+"  "+outcome+"   "+ptl.value (it));
      }
      System.out.println ();
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