X_train_new = pd.concat([train_pred1, train_pred2], axis=1) X_test_new = pd.concat([test_pred1, test_pred2], axis=1) from sklearn.linear_model import Logistic Regression # 导入逻辑回归模型 model = Logistic Regression(random_state=1) model.fit(X_train_new, y_train) # 拟合模型 model.score(df_test, y_test) # 分数评估
