Examples of weka.classifiers.misc.monotone.DiscreteDistribution

weka.classifiers.misc.monotone.DiscreteDistribution

This class represents a discrete probability distribution over a finite number of values.

In the present implementation, objects of type DiscreteDistribution are in fact immutable, so all one can do is create objects and retrieve information, such as median and mean, from them.

This implementation is part of the master's thesis: "Studie en implementatie van instantie-gebaseerde algoritmen voor gesuperviseerd rangschikken", Stijn Lievens, Ghent University, 2004.

@author Stijn Lievens (stijn.lievens@ugent.be) @version $Revision: 1.2 $

      DiscreteEstimator df = 
  (DiscreteEstimator) m_estimatedDistributions.get(cc);
      cc.getValues(attValues);
      switch(m_atype) {
  case AT_MEAN:
    attValues[attValues.length - 1] = (new DiscreteDistribution(df)).mean();
    break;
  case AT_MEDIAN:
    attValues[attValues.length - 1] = (new DiscreteDistribution(df)).median();
    break;
  case AT_MAXPROB:
    attValues[attValues.length - 1] = (new DiscreteDistribution(df)).modes()[0];
    break;
  default: 
    throw new IllegalStateException("Not a valid averaging type");
      }

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Examples of weka.classifiers.misc.monotone.DiscreteDistribution

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