sklearn MLP红酒分类

from sklearn.datasets import load_wine
from sklearn.model_selection import train_test_split

#(1）导入数据
wine = load_wine( )
x, y = wine.data, wine.target

#(2)分割数据
x_train, x_test, y_train, y_test=train_test_split(x,y,test_size = 0.3, random_state = 0 )

#(3）数据预处理
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler().fit(x_train)
x_train = scaler.transform(x_train)
x_test = scaler.transform(x_test) 

 # (4)导入神经网络模型
from sklearn.neural_network import MLPClassifier  

# (5）构建模型︰使用一层网络
model = MLPClassifier(solver="lbfgs", hidden_layer_sizes=(100,))


from sklearn.neural_network import MLPClassifier
model2 = MLPClassifier(solver="lbfgs", hidden_layer_sizes=(100,))
model2.fit(x_train, y_train)
y_predict_on_train = model2.predict(x_train)
y_predict_on_test = model2.predict(x_test)

from sklearn.metrics import accuracy_score
print("训练集合的准确率为：{:.2f}".format(100*accuracy_score(y_train, y_predict_on_train)))
print("测试集合的准确率为：{:.2f}".format(100*accuracy_score(y_test, y_predict_on_test)))
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