Normalizer样本归一化

from sklearn.datasets import load_digits
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import Normalizer, StandardScaler
from sklearn.metrics import accuracy_score
digits = load_digits()
X = digits.data / ____
X_train, X_test, y_train, y_test = train_test_split(____)
n = Normalizer()
s = StandardScaler()
clf1 = MLPClassifier(hidden_layer_sizes=(____,), max_iter=____, random_state=____)
clf1.fit(n.fit_transform(____), y_train)
clf2 = MLPClassifier(hidden_layer_sizes=(____,), max_iter=____, random_state=____)
clf2.fit(s.fit_transform(____), y_train)
print(____)
print(____)