public void classifyTest() { try { CSV2Arff(); java.io.FileReader arrfFile = new java.io.FileReader("D:/final_version/Gesture-Gis-master/GestureGis2/ComparisonFeaturefile.arff"); weka.core.Instances insts = new weka.core.Instances(arrfFile); //weka.core.Instances insts2 = new weka.core.Instances(new java.io.FileReader("D:/Gesture-Gis-master/GestureGis2/ComparisonFeaturefile.arff")); insts.setClassIndex(insts.numAttributes() - 1); //int percentSplit = 66; weka.classifiers.Classifier cl = new weka.classifiers.trees.J48(); //Console.WriteLine("Performing " + percentSplit + "% split evaluation."); //randomize the order of the instances in the dataset. //weka.filters.Filter myRandom = new weka.filters.unsupervised.instance.Randomize(); //myRandom.setInputFormat(insts); //insts = weka.filters.Filter.useFilter(insts, myRandom); int count = insts.numInstances(); int trainSize = count - 1; int testSize = count - trainSize; weka.core.Instances train = new weka.core.Instances(insts, 0, trainSize); cl.buildClassifier(train); //weka.core.Instance current = insts2.instance(0); int numCorrect = 0; /*for (int i = trainSize; i < insts.numInstances(); i++) * { * weka.core.Instance currentInst = insts.instance(i); * double predictedClass = cl.classifyInstance(currentInst); * if (predictedClass == insts.instance(i).classValue()) * numCorrect++; * }*/ int index = count - 1; weka.core.Instance currentInst = insts.instance(index); double predictedClass = cl.classifyInstance(currentInst); int pre = (int)predictedClass; if (predictedClass == insts.instance(index).classValue()) { numCorrect++; } //insts.instance(index).classAttribute(); //insts.attribute(11); string s = insts.toString(); s = s.Substring(s.IndexOf("{") + 1); s = s.Substring(0, s.IndexOf("}")); s = s.Substring(0, s.Length); string[] ae = s.Split(','); /*ArrayList arr = new ArrayList(); * string path_class = @"D:\final_version\Gesture-Gis-master\GestureGis2\Classfile.txt"; * using (StreamReader reader = new StreamReader(path_class)) * { * while (!reader.EndOfStream) * { * arr.Add(reader.ReadLine()); * } * reader.Close(); * }*/ PredictedClassbyWeka = (string)(ae[pre]); arrfFile.close(); //insts.instance(index).attribute(3); /*System.Diagnostics.Debug.WriteLine(numCorrect + " out of " + testSize + " correct (" + * (double)((double)numCorrect / (double)testSize * 100.0) + "%)"); * Console.WriteLine(numCorrect + " out of " + testSize + " correct (" + * (double)((double)numCorrect / (double)testSize * 100.0) + "%)");*/ } catch (java.lang.Exception ex) { ex.printStackTrace(); } }