scores = []
kf = StratifiedKFold(n_splits = 10, random_state = 678)
for train_index, test_index in kf.split(standard_all, Y):
    x_test, x_train = standard_all[test_index], standard_all[train_index]
    y_test, y_train = Y[test_index], Y[train_index]
    clf = KNeighborsClassifier(1, n_jobs = 4)
    clf.fit(x_train, y_train)
    scores.append(clf.score(x_test, y_test))
print("Poszczególne wyniki: ", scores)
print("Błąd wyznaczony procedurą walidacji krzyżowej: ", np.array(scores).mean())