Examples of predictions()

Examples of weka.classifiers.Evaluation.predictions()

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                    if (trainHeader != null) vv.addElement(trainHeader);
                    vv.addElement(m_CurrentVis);
                    if (grph != null) {
                      vv.addElement(grph);
                    }
                    if ((eval != null) && (eval.predictions() != null)) {
                      vv.addElement(eval.predictions());
                      vv.addElement(userTestStructure.classAttribute());
                    }
                    m_History.addObject(name, vv);
                  } else {
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Examples of weka.classifiers.Evaluation.predictions()

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                    vv.addElement(m_CurrentVis);
                    if (grph != null) {
                      vv.addElement(grph);
                    }
                    if ((eval != null) && (eval.predictions() != null)) {
                      vv.addElement(eval.predictions());
                      vv.addElement(userTestStructure.classAttribute());
                    }
                    m_History.addObject(name, vv);
                  } else {
                    FastVector vv = new FastVector();
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Examples of weka.classifiers.Evaluation.predictions()

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                    vv.addElement(grph);
                  }
                }
                vv.addElement(m_CurrentVis);
               
                if ((eval != null) && (eval.predictions() != null)) {
                  vv.addElement(eval.predictions());
                  vv.addElement(inst.classAttribute());
                }
                m_History.addObject(name, vv);
        }
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Examples of weka.classifiers.Evaluation.predictions()

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                  }
                }
                vv.addElement(m_CurrentVis);
               
                if ((eval != null) && (eval.predictions() != null)) {
                  vv.addElement(eval.predictions());
                  vv.addElement(inst.classAttribute());
                }
                m_History.addObject(name, vv);
        }
      } catch (Exception ex) {
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Examples of weka.classifiers.Evaluation.predictions()

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                    if (trainHeader != null) vv.addElement(trainHeader);
                    vv.addElement(m_CurrentVis);
                    if (grph != null) {
                      vv.addElement(grph);
                    }
                    if ((eval != null) && (eval.predictions() != null)) {
                      vv.addElement(eval.predictions());
                      vv.addElement(userTestStructure.classAttribute());
                    }
                    m_History.addObject(name, vv);
                  } else {
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Examples of weka.classifiers.Evaluation.predictions()

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                    vv.addElement(m_CurrentVis);
                    if (grph != null) {
                      vv.addElement(grph);
                    }
                    if ((eval != null) && (eval.predictions() != null)) {
                      vv.addElement(eval.predictions());
                      vv.addElement(userTestStructure.classAttribute());
                    }
                    m_History.addObject(name, vv);
                  } else {
                    FastVector vv = new FastVector();
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Examples of weka.classifiers.Evaluation.predictions()

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        PhaseIwrep.res_graph_xml = ((BayesNet) eval_clas).graph();


        ThresholdCurve tc = new ThresholdCurve();
        Instances tcEachClass[] = new Instances[randData.numClasses()];
        Instances tcResult2 = tc.getCurve(eval_validationE.predictions(),0);
        tcResult2.delete();
        double[] attValues = new double[tcResult2.numAttributes()];
        for (int i = 0; i < attValues.length; i++) {attValues[i] = 1;}
        tcResult2.add(new Instance(1, attValues)); // adds the point 1,1
        for (int i = 0; i < attValues.length; i++) {attValues[i] = 0;}
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Examples of weka.classifiers.Evaluation.predictions()

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        //        PhaseIwrep.res_ROC_curves = new double[randData.numClasses()][2][tcEachClass.numInstances()];
            Plot2D myPlot2Db = new Plot2D();
            tc = new ThresholdCurve();
           
        for (int class_index =0 ; class_index< randData.numClasses();class_index++){
            tcEachClass[class_index] = tc.getCurve(eval_validationE.predictions(),class_index); // Uses Class 0-end
        }
        
           
        double[][] CL4 = new double[tcEachClass[0].numInstances()][randData.numClasses()];
        double[][] CL5 = new double[tcEachClass[0].numInstances()][randData.numClasses()];
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