Java tutorial
/* * This program is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. */ /* * Example.java * Copyright (C) 2005 Yasser EL-Manzalawy * */ /* * This exmaple deomnstrates how to use WLSVM classifier. */ import weka.classifiers.Evaluation; import wlsvm.WLSVM; public class Example { public static void main(String[] argv) throws Exception { if (argv.length < 1) { System.out.println("Usage: Example <arff file>"); System.exit(1); } String dataFile = argv[0]; // input arff file WLSVM lib = new WLSVM(); String[] ops = { new String("-t"), dataFile, new String("-x"), // 5 folds CV new String("5"), new String("-i"), // //--------------- new String("-S"), // WLSVM options new String("0"), // Classification problem new String("-K"), // RBF kernel new String("2"), new String("-G"), // gamma new String("1"), new String("-C"), // C new String("7"), new String("-Z"), // normalize input data new String("1"), new String("-M"), // cache size in MB new String("100") }; System.out.println(Evaluation.evaluateModel(lib, ops)); } }