System.out.println(plotInstances);
  public static void processClassifierPrediction(Instance toPredict,                                           Classifier classifier,					   Evaluation eval,					   FastVector predictions,					   Instances plotInstances,					   FastVector plotShape,					   FastVector plotSize) {    try {      double pred;      // classifier is a distribution classifier and class is nominal      if (predictions != null) {	Instance classMissing = (Instance)toPredict.copy();	classMissing.setDataset(toPredict.dataset());	classMissing.setClassMissing();	Classifier dc = classifier;	double [] dist = 	  dc.distributionForInstance(classMissing);	pred = eval.evaluateModelOnce(dist, toPredict);	predictions.addElement(new 	  NominalPrediction(toPredict.classValue(), dist, toPredict.weight()));      } else {	pred = eval.evaluateModelOnce(classifier, 				      toPredict);      }      double [] values = new double[plotInstances.numAttributes()];      System.out.println(plotInstances);      for (int i = 0; i < plotInstances.numAttributes(); i++) {          System.out.println(toPredict.classIndex());          System.out.println(toPredict.dataset());	if (i < toPredict.classIndex()) {	  values[i] = toPredict.value(i);	} else if (i == toPredict.classIndex()) {	  values[i] = pred;	  values[i+1] = toPredict.value(i);	  /* // if the class value of the instances to predict is missing then	  // set it to the predicted value	  if (toPredict.isMissing(i)) {	    values[i+1] = pred;	    } */	  i++;	} else {	  values[i] = toPredict.value(i-1);	}      }      plotInstances.add(new Instance(1.0, values));      if (toPredict.classAttribute().isNominal()) {	if (toPredict.isMissing(toPredict.classIndex()) 	    || Instance.isMissingValue(pred)) {	  plotShape.addElement(new Integer(Plot2D.MISSING_SHAPE));	} else if (pred != toPredict.classValue()) {	  // set to default error point shape	  plotShape.addElement(new Integer(Plot2D.ERROR_SHAPE));	} else {	  // otherwise set to constant (automatically assigned) point shape	  plotShape.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));	}	plotSize.addElement(new Integer(Plot2D.DEFAULT_SHAPE_SIZE));      } else {	// store the error (to be converted to a point size later)	Double errd = null;	if (!toPredict.isMissing(toPredict.classIndex()) && 	    !Instance.isMissingValue(pred)) {	  errd = new Double(pred - toPredict.classValue());	  plotShape.addElement(new Integer(Plot2D.CONST_AUTOMATIC_SHAPE));	} else {	  // missing shape if actual class not present or prediction is missing	  plotShape.addElement(new Integer(Plot2D.MISSING_SHAPE));	}	plotSize.addElement(errd);      }    } catch (Exception ex) {      ex.printStackTrace();    }  }