我想创建一个循环来比较机器学习模型的分数，但生成了“解包的值过多（预期2）”的错误。如何解决这个问题？

from sklearn.linear_model import LinearRegressionfrom sklearn.linear_model import Ridgefrom sklearn.linear_model import Lassofrom sklearn.linear_model import ElasticNetfrom sklearn.ensemble import GradientBoostingRegressornames=[]train_scores =[]test_score =[]models={'OLS': LinearRegression(),       'Ridge': Ridge(),       'Lasso': Lasso(),       'ElasticN': ElasticNet(),       'GBReg': GradientBoostingRegressor()}for name, model in models:    name_model = model    name_fit = name_model.fit(X_train, y_train)    name_pred = name_model.predict(X_test)    name_train_score = name_model.score(X_train, y_train).round(4)    name_test_score = name_model.score(X_test, y_test).round(4)    names.append(name)    train_scores.append(name_train_score)    test_scores.append(name_test_score)score_df = pd.DataFrame(names, train_scores, test_scores)score_df

回答：

你好，这是因为你在遍历一个字典。字典存储键值对。如果你想同时访问键和值，可以在字典后面加上.items()。

for name, model in models.items():

如需进一步阅读，请查看这个！