Wine数据集基础分类

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
from sklearn.metrics import accuracy_score
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)
clf = MLPClassifier(hidden_layer_sizes=(20,10), max_iter=500, random_state=42)
clf.fit(X_train, y_train)
print(f'准确率: {accuracy_score(y_test, clf.predict(X_test)):.4f}')