容忍度tol设置

from sklearn.datasets import load_wine
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
wine = load_wine()
X_train, X_test, y_train, y_test = train_test_split(wine.data, wine.target, test_size=0.2, random_state=42)
scaler = StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.transform(X_test)
for tol in [1e-2, 1e-4, 1e-6]:
    clf = MLPClassifier(hidden_layer_sizes=(20,), max_iter=500, tol=tol, random_state=42)
    clf.fit(X_train, y_train)
    print(f'tol={tol}: 迭代={clf.n_iter_}')