try
{
BufferedReader trainReader = new BufferedReader(new FileReader(“train.arff”));//File with text examples
BufferedReader classifyReader = new BufferedReader(new FileReader(“test.arff”));//File with text to classify
Instances trainInsts = new Instances(trainReader);
Instances classifyInsts = new Instances(classifyReader);
trainInsts.setClassIndex(trainInsts.numAttributes() – 1);
classifyInsts.setClassIndex(classifyInsts.numAttributes() -1);
FilteredClassifier model = new FilteredClassifier();
StringToWordVector stringtowordvector = new StringToWordVector();
stringtowordvector.set_UseStoplist(true);
stringtowordvector.set_OnlyAlphabeticTokens(true);
model.setFilter(new StringToWordVector());
model.setClassifier(new NaiveBayes());
model.buildClassifier(trainInsts);
//System.out.println(model);
for (int i = 0; i < classifyInsts.numInstances(); i++)
{
classifyInsts.instance(i).setClassMissing();
double cls = model.classifyInstance(classifyInsts.instance(i));
classifyInsts.instance(i).setClassValue(cls);
}
System.out.println(classifyInsts);
}
catch (Exception o)
{
System.err.println(o.getMessage());
}
