1 from sklearn.datasets import load_wine
2 from sklearn.model_selection import train_test_split
3 import numpy as np
4 wine_dataset=load_wine()
5 X,y=wine_dataset['data'],wine_dataset['target']
6 X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3)
7
8 from sklearn.preprocessing import StandardScaler
9 ss=StandardScaler()
10 ss.fit(X_train)
11 X_train=ss.transform(X_train)
12 X_test=ss.transform(X_test)
13
14 from sklearn.linear_model import LogisticRegression
15 model=LogisticRegression().fit(X_train,y_train)
16 print("the score of this model：{}".format(model.score(X_test,y_test)))
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