"值太多，无法解包"，同时迭代 for 循环

Question

我正在预测算法中迭代多重回归模型。当我从一个列表中迭代模型时，没有这样的错误。但是，当我遍历两个列表时，一个用于模型("classifiers"(，另一个用于作为字符串的模型名称('ListOfclassifiers'(，我会得到一个错误，如：'ValueError: too many values to unpack (expected 2)'

ListOfclassifiers = ['svm.SVR', 'SGDRegressor', 'BayesianRidge', 'LassoLars', 'ARDRegression',
'PassiveAggressiveRegressor',
'TheilSenRegressor', 'LinearRegression']
classifiers = [svm.SVR(),
linear_model.SGDRegressor(),
linear_model.BayesianRidge(),
linear_model.LassoLars(),
linear_model.ARDRegression(),
linear_model.PassiveAggressiveRegressor(),
linear_model.TheilSenRegressor(),
linear_model.LinearRegression()]
for items, types in classifiers, ListOfclassifiers:
clf = items
clf.fit(X_train, y_train)
clf.score(X_test, y_test)
accuracy = clf.score(X_test, y_test)
print('The accuracy with', types, 'is:', accuracy)

Answer 1

用zip方法合并两个数组：

for items, types in zip(classifiers, ListOfclassifiers):
# todo smth