Examples of cc.mallet.types.Multinomial

cc.mallet.types.Multinomial
A probability distribution over a set of features represented as a {@link cc.mallet.types.FeatureVector}. The values associated with each element in the Multinomial/FeaturVector are probabilities and should sum to 1. Features are indexed using feature indices - the index into the underlying Alphabet - rather than using locations the way FeatureVectors do.
{@link cc.mallet.types.Multinomial.Estimator} provides a subhierachyof ways to generate an estimate of the probability distribution from counts associated with the features. @author Andrew McCallum mccallum@cs.umass.edu

  }


  public void testMultinomial ()
  {
    double[] c = new double[] {.2, .3, .1, .4};
    Multinomial m = new Multinomial (c);
    assertTrue (m.probability (0) == .2);
  }

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    Dirichlet dirichlet = new Dirichlet (new double[] { 1, 1, 1, 1 });


    FactorGraph mdl = new FactorGraph (vars);
    for (int i = 0; i < length - 1; i++) {
      Multinomial m = dirichlet.randomMultinomial (r);
      double[] probs = m.getValues ();
      mdl.addFactor (vars[i], vars[i + 1], probs);
    }


    return mdl;
  }

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    return pr;
  }


  public Multinomial randomMultinomial (Randoms r)
  {
    return new Multinomial (randomRawMultinomial(r), dict, partition.length, false, false);
  }

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    return new Dirichlet (pr, dict);
  }


  public FeatureSequence randomFeatureSequence (Randoms r, int length)
  {
    Multinomial m = randomMultinomial (r);
    return m.randomFeatureSequence (r, length);
  }

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Related Classes of cc.mallet.types.Multinomial

cc.mallet.fst.FeatureTransducer

cc.mallet.fst.FeatureTransducer$State

cc.mallet.fst.HMM

cc.mallet.grmm.inference.RandomGraphs

cc.mallet.types.Dirichlet

cc.mallet.types.FeatureSequence

cc.mallet.types.FeatureVector

cc.mallet.types.tests.TestMultinomial

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