def algo(per_noisy = 0.3, per_Vclean = 0.5):
    iris = load_iris()
    X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, random_state=42)

    # Bruitage des per_noisy etiquettes
    N = len(y_train)
    nb_noisy = int(N * per_noisy)
    for i in range(nb_noisy):
        r = random.randrange(3)
        while y_train[i] == r:
            r = random.randrange(3)
        y_train[i] = r

    # Création des listes
    nb_Vclean = int((N - nb_noisy) * per_Vclean)
    Tnoisy = [X_train[:nb_noisy], y_train[:nb_noisy]]
    Vclean = [X_train[nb_noisy:nb_noisy+nb_Vclean], y_train[nb_noisy:nb_noisy+nb_Vclean]]
    Tclean = [X_train[nb_noisy+nb_Vclean:], y_train[nb_noisy+nb_Vclean:]]
    Uclean = [X_test, y_test]

    return Tnoisy, Vclean, Tclean, Uclean