Java tutorial
/* * To change this license header, choose License Headers in Project Properties. * To change this template file, choose Tools | Templates * and open the template in the editor. */ package personality_prediction; import weka.core.Instances; import java.io.BufferedReader; import java.io.BufferedWriter; import java.io.File; import java.io.FileReader; import java.io.FileWriter; import java.util.Scanner; import weka.classifiers.trees.J48; import weka.core.converters.ArffSaver; import weka.core.converters.CSVLoader; /** * * @author somya */ public class Classifier { /** * @param args the command line arguments */ void run_classifier() { // TODO code application logic here try { //csv2arff(); System.out.println("Enter the class for which you want to classify"); System.out.println("1..Openness"); System.out.println("2..Neuroticism"); System.out.println("3..Agreeableness"); System.out.println("4..Conscientiousness"); System.out.println("5..Extraversion"); System.out.println(); Scanner sc = new Scanner(System.in); int choice = sc.nextInt(); String filename = ""; // BufferedReader reader=new BufferedReader(new FileReader("")); if (choice == 1) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_open.arff"; //reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_open.arff")); } else if (choice == 2) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_neur.arff"; // reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_neur.arff")); } else if (choice == 3) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_agr.arff"; // reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_agr.arff")); } else if (choice == 4) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_con.arff"; // reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_con.arff")); } else if (choice == 5) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_extr.arff"; // reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\Training_data_extr.arff")); } //BufferedReader reader = new BufferedReader(new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Training dataset\\")); // DataSource source = new DataSource("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_Dataset\\Features_value.arff"); //Instances data = source.getDataSet(); BufferedReader reader = new BufferedReader(new FileReader(filename)); Instances data = new Instances(reader); reader.close(); //******88setting class attribute************ data.setClassIndex(data.numAttributes() - 1); // OptionsToCode option=new OptionsToCode(); // String options[]={"java","ExperimentDemo","-classifier weka.classifiers.trees.M5P","-exptype regression","-splittype randomsplit","-runs 10", //"-percentage 66","-result /some/where/results.arff","-t bolts.arff","-t bodyfat.arff"}; // String[] options={"weka.classifiers.functions.SMO"}; //String[] options={"weka.classifiers.trees.M5P"}; //option.convert(options); //*******************building a classifier********************* String[] options = new String[1]; options[0] = "-U"; // unpruned tree J48 tree = new J48(); // new instance of tree tree.setOptions(options); // set the options tree.buildClassifier(data); // build classifier if (choice == 1) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_open.arff"; //fr=new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_open.arff"); } else if (choice == 2) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_neur.arff"; //fr=new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_neur.arff"); } else if (choice == 3) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_agr.arff"; // fr=new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_agr.arff"); } else if (choice == 4) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_con.arff"; //fr=new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_con.arff"); } else if (choice == 5) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_extr.arff"; //fr=new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_extr.arff"); } FileReader fr = new FileReader(filename); BufferedReader br = new BufferedReader(fr); Instances unlabeled = new Instances(br); /// Instances unlabeled = new Instances( // new BufferedReader( // new FileReader("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_Dataset\\experiment\\test_data_unlabelled.arff"))); // set class attribute unlabeled.setClassIndex(unlabeled.numAttributes() - 1); // create copy Instances labeled = new Instances(unlabeled); // label instances for (int i = 0; i < unlabeled.numInstances(); i++) { double clsLabel = tree.classifyInstance(unlabeled.instance(i)); labeled.instance(i).setClassValue(clsLabel); } // save labeled data if (choice == 1) { filename = "C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_open_labelled.arff"; // fr1=new FileWriter("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_open123.arff"); } else if (choice == 2) { // fr1=new FileWriter("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_neur_labelled.arff"); } else if (choice == 3) { // fr1=new FileWriter("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_agr_labelled.arff"); } else if (choice == 4) { //fr1=new FileWriter("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_con_labelled.arff"); } else if (choice == 5) { // fr1=new FileWriter("C:\\Users\\somya\\Desktop\\Personality Mining\\WEKA_DataSet\\Labelling\\Testing_data_extr_labelled.arff"); } FileWriter fr1 = new FileWriter(filename); BufferedWriter writer = new BufferedWriter(fr1); writer.write(labeled.toString()); writer.newLine(); writer.flush(); writer.close(); } catch (Exception e) { System.out.println(e.getLocalizedMessage()); } } void csv2arff() { try { CSVLoader loader = new CSVLoader(); loader.setSource( new File("C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_Dataset\\Features_value.csv")); Instances data = loader.getDataSet(); // save ARFF File f = new File("C:\\Users\\divya\\Desktop\\Personality Mining\\WEKA_Dataset\\Features_value.arff"); ArffSaver saver = new ArffSaver(); saver.setInstances(data); saver.setFile(f); //saver.setDestination(f); saver.writeBatch(); } catch (Exception e) { System.out.println(e.getLocalizedMessage()); } } }//end of class