Firstly, I'd like to say there are so many methods to solve the problem. The solution I mentioned is quite simple, but other answers from StackOverflow are not detailed descripted, with waste my too much time to verify. So I'm happy to share it with all WEKA beginners :)
a) Download the LibSVM.jar from Maven Repository Center. Note that this LibSVM.jar
is different from the libsvm.jar
developed by Chih-Chung Chang and Chih-Jen Lin;
b) Add the LibSVM.jar
to the classpath of our Java project;
c) Call the classifier LibSVM when you need, see the following Java code.
import weka.classifiers.functions.LibSVM; // contained in LibSVM.jar
String path = "file/train.arff";
Instances train = DataSource.read(path); // load the dataset
train.setClassIndex(train.numAttribute()-1); // set class index
LibSVM svm = new LibSVM(); // load the svm classifier
svm.buildClassifier(train);
Evaluation eval = new Evaluation(train);
eval.crossValidateModel(svm, train, 10, new Random(1)); // 10-fold cross-validation