Package weka.classifiers

Class StoppableEvaluation

  • All Implemented Interfaces:
    adams.core.Stoppable, adams.core.StoppableWithFeedback, Serializable, weka.core.RevisionHandler, weka.core.Summarizable
    public class StoppableEvaluation
extends weka.classifiers.Evaluation
implements adams.core.StoppableWithFeedback
    Extended Evaluation class that can stop its evaluation processes better.
    Author:
    fracpete (fracpete at waikato dot ac dot nz)
    See Also:
    Serialized Form

    • Field Summary

      • Fields inherited from class weka.classifiers.Evaluation

        BUILT_IN_EVAL_METRICS, m_delegate

    • Constructor Summary

      Constructors 
      Constructor Description
      StoppableEvaluation​(weka.core.Instances data)
      Initializes all the counters for the evaluation.
      StoppableEvaluation​(weka.core.Instances data, weka.classifiers.CostMatrix costMatrix)
      Initializes all the counters for the evaluation and also takes a cost matrix as parameter.

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      boolean isStopped()
      Whether the execution has been stopped.
      void stopExecution()
      Stops the execution.

      • Methods inherited from class weka.classifiers.Evaluation

        areaUnderPRC, areaUnderROC, avgCost, confusionMatrix, correct, correlationCoefficient, coverageOfTestCasesByPredictedRegions, crossValidateModel, crossValidateModel, equals, errorRate, evaluateModel, evaluateModel, evaluateModel, evaluateModelOnce, evaluateModelOnce, evaluateModelOnce, evaluateModelOnceAndRecordPrediction, evaluateModelOnceAndRecordPrediction, evaluationForSingleInstance, falseNegativeRate, falsePositiveRate, fMeasure, getAllEvaluationMetricNames, getClassPriors, getDiscardPredictions, getHeader, getMetricsToDisplay, getPluginMetric, getPluginMetrics, getRevision, incorrect, kappa, KBInformation, KBMeanInformation, KBRelativeInformation, main, matthewsCorrelationCoefficient, meanAbsoluteError, meanPriorAbsoluteError, numFalseNegatives, numFalsePositives, numInstances, numTrueNegatives, numTruePositives, pctCorrect, pctIncorrect, pctUnclassified, precision, predictions, priorEntropy, recall, relativeAbsoluteError, rootMeanPriorSquaredError, rootMeanSquaredError, rootRelativeSquaredError, setDiscardPredictions, setMetricsToDisplay, setPriors, SFEntropyGain, SFMeanEntropyGain, SFMeanPriorEntropy, SFMeanSchemeEntropy, SFPriorEntropy, SFSchemeEntropy, sizeOfPredictedRegions, toClassDetailsString, toClassDetailsString, toCumulativeMarginDistributionString, toggleEvalMetrics, toMatrixString, toMatrixString, toSummaryString, toSummaryString, toSummaryString, totalCost, trueNegativeRate, truePositiveRate, unclassified, unweightedMacroFmeasure, unweightedMicroFmeasure, updatePriors, useNoPriors, weightedAreaUnderPRC, weightedAreaUnderROC, weightedFalseNegativeRate, weightedFalsePositiveRate, weightedFMeasure, weightedMatthewsCorrelation, weightedPrecision, weightedRecall, weightedTrueNegativeRate, weightedTruePositiveRate, wekaStaticWrapper

    • Constructor Detail

      • StoppableEvaluation

        public StoppableEvaluation​(weka.core.Instances data)
                    throws Exception
        Initializes all the counters for the evaluation. Use useNoPriors() if the dataset is the test set and you can't initialize with the priors from the training set via setPriors(Instances).
        Parameters:
        data - set of training instances, to get some header information and prior class distribution information
        Throws:
        Exception - if the class is not defined
        See Also:
        Evaluation.useNoPriors(), Evaluation.setPriors(Instances)

      • StoppableEvaluation

        public StoppableEvaluation​(weka.core.Instances data,
                           weka.classifiers.CostMatrix costMatrix)
                    throws Exception
        Initializes all the counters for the evaluation and also takes a cost matrix as parameter. Use useNoPriors() if the dataset is the test set and you can't initialize with the priors from the training set via setPriors(Instances).
        Parameters:
        data - set of training instances, to get some header information and prior class distribution information
        costMatrix - the cost matrix---if null, default costs will be used
        Throws:
        Exception - if cost matrix is not compatible with data, the class is not defined or the class is numeric
        See Also:
        Evaluation.useNoPriors(), Evaluation.setPriors(Instances)

    • Method Detail

      • stopExecution

        public void stopExecution()
        Stops the execution. No message set.
        Specified by:
        stopExecution in interface adams.core.Stoppable

      • isStopped

        public boolean isStopped()
        Whether the execution has been stopped.
        Specified by:
        isStopped in interface adams.core.StoppableWithFeedback
        Returns:
        true if stopped