def train( train_data_dir, labels, sample_num ): f_index, y, X = FeatureFactor.getFeatureSpace( train_data_dir, labels, sample_num ) saveTheFSpace( f_index ) model = Libsvm.train( y, X ) Libsvm.saveModel( model )
def train(train_data_dir, labels, sample_num): f_index, y, X = FeatureFactor.getFeatureSpace(train_data_dir, labels, sample_num) saveTheFSpace(f_index) model = Libsvm.train(y, X) Libsvm.saveModel(model)
''' Created on May 20, 2013 @author: jacob ''' import Libsvm Libsvm.train("subset1000", "subset1000")