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)))