Examples of weka.classifiers.functions.pace.NormalMixture

weka.classifiers.functions.pace.NormalMixture

Class for manipulating normal mixture distributions.

For more information see:

Wang, Y (2000). A new approach to fitting linear models in high dimensional spaces. Hamilton, New Zealand.

Wang, Y., Witten, I. H.: Modeling for optimal probability prediction. In: Proceedings of the Nineteenth International Conference in Machine Learning, Sydney, Australia, 650-657, 2002. BibTeX:

 @phdthesis{Wang2000, address = {Hamilton, New Zealand}, author = {Wang, Y}, school = {Department of Computer Science, University of Waikato}, title = {A new approach to fitting linear models in high dimensional spaces}, year = {2000} } @inproceedings{Wang2002, address = {Sydney, Australia}, author = {Wang, Y. and Witten, I. H.}, booktitle = {Proceedings of the Nineteenth International Conference in Machine Learning}, pages = {650-657}, title = {Modeling for optimal probability prediction}, year = {2002} }

@author Yong Wang (yongwang@cs.waikato.ac.nz) @version $Revision: 1.5 $

    DoubleVector aTilde = null;
    switch( paceEstimator) {
    case ebEstimator: 
    case nestedEstimator:
    case subsetEstimator:
      NormalMixture d = new NormalMixture();
      d.fit( aHat, MixtureDistribution.NNMMethod ); 
      if( paceEstimator == ebEstimator ) 
  aTilde = d.empiricalBayesEstimate( aHat );
      else if( paceEstimator == ebEstimator ) 
  aTilde = d.subsetEstimate( aHat );
      else aTilde = d.nestedEstimate( aHat );
      break;
    case pace2Estimator: 
    case pace4Estimator:
    case pace6Estimator:
      DoubleVector AHat = aHat.square();

    DoubleVector aTilde = null;
    switch( paceEstimator) {
    case ebEstimator: 
    case nestedEstimator:
    case subsetEstimator:
      NormalMixture d = new NormalMixture();
      d.fit( aHat, MixtureDistribution.NNMMethod ); 
      if( paceEstimator == ebEstimator ) 
  aTilde = d.empiricalBayesEstimate( aHat );
      else if( paceEstimator == ebEstimator ) 
  aTilde = d.subsetEstimate( aHat );
      else aTilde = d.nestedEstimate( aHat );
      break;
    case pace2Estimator: 
    case pace4Estimator:
    case pace6Estimator:
      DoubleVector AHat = aHat.square();

Related Classes of weka.classifiers.functions.pace.NormalMixture

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