Package weka.gui.explorer

Examples of weka.gui.explorer.ClassifierErrorsPlotInstances


            +")...");
        m_visual.setAnimated();
      }
      try {

        ClassifierErrorsPlotInstances plotInstances =
          ExplorerDefaults.getClassifierErrorsPlotInstances();
        Evaluation eval = null;

        if (m_trainData == null || m_trainData.numInstances() == 0) {
          eval = new Evaluation(m_testData);
          plotInstances.setInstances(m_testData);
          plotInstances.setClassifier(m_classifier);
          plotInstances.setClassIndex(m_testData.classIndex());
          plotInstances.setEvaluation(eval);
          eval = adjustForInputMappedClassifier(eval, m_classifier,
              m_testData, plotInstances);
         
          eval.useNoPriors();
        } else {
          eval = new Evaluation(m_trainData);
          plotInstances.setInstances(m_trainData);
          plotInstances.setClassifier(m_classifier);
          plotInstances.setClassIndex(m_trainData.classIndex());
          plotInstances.setEvaluation(eval);
          eval = adjustForInputMappedClassifier(eval, m_classifier,
              m_trainData, plotInstances);
        }
       
        plotInstances.setUp();
       
        for (int i = 0; i < m_testData.numInstances(); i++) {
          if (m_stopped) {
            break;
          }
          Instance temp = m_testData.instance(i);
          plotInstances.process(temp, m_classifier, eval);
        }
       
        if (m_stopped) {
          return;
        }
View Full Code Here


            +"Evaluating (" + m_setNum
            +")...");
      }
      try {

        ClassifierErrorsPlotInstances plotInstances =
          ExplorerDefaults.getClassifierErrorsPlotInstances();
        Evaluation eval = null;

        if (m_trainData == null || m_trainData.numInstances() == 0) {
          eval = new Evaluation(m_testData);
          plotInstances.setInstances(m_testData);
          plotInstances.setClassifier(m_classifier);
          plotInstances.setClassIndex(m_testData.classIndex());
          plotInstances.setEvaluation(eval);
          eval = adjustForInputMappedClassifier(eval, m_classifier,
              m_testData, plotInstances);
         
          eval.useNoPriors();
        } else {
          eval = new Evaluation(m_trainData);
          plotInstances.setInstances(m_trainData);
          plotInstances.setClassifier(m_classifier);
          plotInstances.setClassIndex(m_trainData.classIndex());
          plotInstances.setEvaluation(eval);
          eval = adjustForInputMappedClassifier(eval, m_classifier,
              m_trainData, plotInstances);
        }
       
        plotInstances.setUp();
       
        for (int i = 0; i < m_testData.numInstances(); i++) {
          if (m_stopped) {
            break;
          }
          Instance temp = m_testData.instance(i);
          plotInstances.process(temp, m_classifier, eval);
        }
       
        if (m_stopped) {
          return;
        }
View Full Code Here

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