function model = ClassifierTrain(data,type)

% Training the classifier that would do the sample selection

javaaddpath('weka.jar');

CSVtoARFF(data,'train','train');

train_file = 'train.arff';

reader = javaObject('java.io.FileReader', train_file);

train = javaObject('weka.core.Instances', reader);

train.setClassIndex(train.numAttributes() - 1);

% options = javaObject('java.lang.String');

switch type

    case 'svm'

        model = javaObject('weka.classifiers.functions.SMO');

        kernel = javaObject('weka.classifiers.functions.supportVector.RBFKernel');

        model.setKernel(kernel);

    case 'tree'

        model = javaObject('weka.classifiers.trees.J48');

        % options = weka.core.Utils.splitOptions('-C 0.2');

        % model.setOptions(options);

    case 'knn'

        model = javaObject('weka.classifiers.lazy.IBk');

        model.setKNN(5);

    case 'logistic'

        model = javaObject('weka.classifiers.functions.Logistic');

end

model.buildClassifier(train);