X, y = get_data(split=False)

k = 3
splits = cross_validation(X, y, k)
sum_acc = 0
for i in range(k):
    x_train, y_train, x_test, y_test = splits[i]
    svm = SVC(gamma = best_gamma)
    svm.fit(x_train, y_train)
    test_acc = svm.score(x_test, y_test)
    sum_acc += test_acc
cv_accuracy = sum_acc / k
cv_accuracy