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RandomForest.computeAverageImpurityDecreasePerAttribute
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How to use
computeAverageImpurityDecreasePerAttribute
method
in
weka.classifiers.trees.RandomForest

Best Java code snippets using weka.classifiers.trees.RandomForest.computeAverageImpurityDecreasePerAttribute (Showing top 2 results out of 315)

origin: Waikato/weka-trunk

double[] nodeCounts = new double[m_data.numAttributes()];
double[] impurityScores =
 computeAverageImpurityDecreasePerAttribute(nodeCounts);
int[] sortedIndices = Utils.sort(impurityScores);
buffer
origin: nz.ac.waikato.cms.weka/weka-stable

double[] nodeCounts = new double[m_data.numAttributes()];
double[] impurityScores =
 computeAverageImpurityDecreasePerAttribute(nodeCounts);
int[] sortedIndices = Utils.sort(impurityScores);
buffer
weka.classifiers.treesRandomForestcomputeAverageImpurityDecreasePerAttribute

Javadoc

Computes the average impurity decrease per attribute over the trees

Popular methods of RandomForest

  • <init>
    Constructor that sets base classifier for bagging to RandomTre and default number of iterations to 1
  • defaultClassifierString
    String describing default classifier.
  • defaultNumberOfIterations
    The default number of iterations to perform.
  • getBagSizePercent
  • getCalcOutOfBag
  • getClassifier
  • getComputeAttributeImportance
    Get whether to compute and output attribute importance scores
  • getDoNotCheckCapabilities
  • getNumDecimalPlaces
  • getNumExecutionSlots
  • getNumIterations
  • getOutputOutOfBagComplexityStatistics
  • getNumIterations,
  • getOutputOutOfBagComplexityStatistics,
  • getPrintClassifiers,
  • getStoreOutOfBagPredictions,
  • getTechnicalInformation,
  • runClassifier,
  • setBagSizePercent,
  • setBatchSize,
  • setCalcOutOfBag

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