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EM.getMinLogLikelihoodImprovementCV
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How to use
getMinLogLikelihoodImprovementCV
method
in
weka.clusterers.EM

Best Java code snippets using weka.clusterers.EM.getMinLogLikelihoodImprovementCV (Showing top 2 results out of 315)

origin: Waikato/weka-trunk

result.add("" + getMaximumNumberOfClusters());
result.add("-ll-cv");
result.add("" + getMinLogLikelihoodImprovementCV());
result.add("-ll-iter");
result.add("" + getMinLogLikelihoodImprovementIterating());
origin: nz.ac.waikato.cms.weka/weka-stable

result.add("" + getMaximumNumberOfClusters());
result.add("-ll-cv");
result.add("" + getMinLogLikelihoodImprovementCV());
result.add("-ll-iter");
result.add("" + getMinLogLikelihoodImprovementIterating());
weka.clusterersEMgetMinLogLikelihoodImprovementCV

Javadoc

Get the minimum improvement in cross-validated log likelihood required to consider increasing the number of clusters when cross-validating to find the best number of clusters

Popular methods of EM

  • <init>
    Constructor.
  • setNumClusters
    Set the number of clusters (-1 to select by CV).
  • CVClusters
    estimate the number of clusters by cross validation on the training data.
  • E
    The E step of the EM algorithm. Estimate cluster membership probabilities.
  • EM_Init
    Initialize the global aggregated estimators and storage.
  • EM_Report
    verbose output for debugging
  • M
    The M step of the EM algorithm.
  • M_reEstimate
  • buildClusterer
    Generates a clusterer. Has to initialize all fields of the clusterer that are not being set via opti
  • distributionForInstance
  • doEM
    Perform the EM algorithm
  • estimate_priors
    calculate prior probabilites for the clusters
  • doEM,
  • estimate_priors,
  • getCapabilities,
  • getMaximumNumberOfClusters,
  • getMinLogLikelihoodImprovementIterating,
  • getMinStdDev,
  • getNumClusters,
  • getNumExecutionSlots,
  • getNumFolds

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