Examples of weka.classifiers.timeseries.eval.ErrorModule

Package weka.classifiers.timeseries.eval

Examples of weka.classifiers.timeseries.eval.ErrorModule

weka.classifiers.timeseries.eval.ErrorModule
Superclass of error-based evaluation modules. Stores the predictions for each target along with the actual values. Computes the sum of errors for each target. @author Mark Hall (mhall{[at]}pentaho{[dot]}com) @version $Revision: 49983 $


      // ignore out of range steps
      if (i < 0 || i >= preds.size()) {
        continue;
      }
      ErrorModule predsForStepI = preds.get(i);
      List<NumericPrediction> predsForTargetAtI = predsForStepI
          .getPredictionsForTarget(targetName);


      String step = "-steps";
      if (i == 0) {
        step = "-step";

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      AbstractForecaster.stringToList(forecaster.getFieldsToForecast());
    m_confidenceLevel = confidenceLevel;
    
    List<ErrorModule> confidenceCalculators = new ArrayList<ErrorModule>();
    for (int i = 0; i < numSteps; i++) {
      ErrorModule m = new ErrorModule();
      m.setTargetFields(m_targetFields);
      confidenceCalculators.add(m);
    }
    
    Instances primeInsts = new Instances(insts, 0, numPrime);
/*    for (int i = 0; i < numPrime; i++) {

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Related Classes of weka.classifiers.timeseries.eval.ErrorModule

weka.classifiers.evaluation.NumericPrediction

weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

weka.classifiers.timeseries.eval.graph.JFreeChartDriver

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