多模型GridSearchCV

Question

我正在尝试创建一个GridSearch简历函数，它需要一个以上的模型。但是，我有以下错误: TypeError:不是所有在字符串格式化期间转换的参数

def grid(model, X_train,y_train):
    grid_search = GridSearchCV(model, parameters, cv=5)
    grid_search.fit(X_train, y_train)
    prediction = grid_search.predict(X_test)
    best_classifier = grid_search.best_estimator_

    return grid_search

clf = [('DecisionTree',DT()),('RandomForest',RF())

n_folds = 15

for model in clf:
    
    print('\nWorking on ', model[0])
    
    grid_search = grid(model,X_train,y_train)

Answer 1

您已经将模型存储在元组列表中(请注意，在您的示例中，结束括号实际上缺少)：

clf = [('DecisionTree', DT()), ('RandomForest', RF())]

由于迭代了所有元组，并且实际模型存储在每个元组的索引1中，所以必须将model[1]传递给函数：

for model in clf:
    print('\nWorking on ', model[0])
    grid_search = grid(model[1], X_train, y_train) # <-- change in this line