scikit

def train(dataSet, target):
	clf = svm.SVC(gamma=0.00000001, probability=True, C=1000000, verbose=True, tol=1e-10, cache_size=600, kernel='rbf', 
              class_weight='balanced')
	n_samples = len(dataSet)
	a = np.array(dataSet)
	b = np.array(target)
	print b
	x_train, x_test, y_train, y_test = model_selection.train_test_split(a, b, test_size=0.20)
	clf.fit(x_train[:n_samples], y_train[:n_samples])
	joblib.dump(clf, 'trained_alpha_clf.pkl')