AttributeError: 'GridSearchCV' object has no attribute 'best_params_'

Question

网格搜索是一种从我们指定的组合中为任何模型找到最佳参数的方法。我已经按照以下方式对我的模型进行了网格搜索，并希望找到使用此网格搜索确定的最佳参数。

from sklearn.model_selection import GridSearchCV
# Create the parameter grid based on the results of random search 
param_grid = {
    'bootstrap': [True],'max_depth': [20,30,40, 100, 110],
    'max_features': ['sqrt'],'min_samples_leaf': [5,10,15],
    'min_samples_split': [40,50,60], 'n_estimators': [150, 200, 250]
}
# Create a based model
rf = RandomForestClassifier()
# Instantiate the grid search model
grid_search = GridSearchCV(estimator = rf, param_grid = param_grid, 
                          cv = 3, n_jobs = -1, verbose = 2)

现在我想找到网格搜索的最佳参数作为输出

grid_search.best_params_

错误:

----> grid_search.best_params_
AttributeError: 'GridSearchCV' object has no attribute 'best_params_'

我错过了什么？

Answer 1

不拟合数据就无法获得最佳参数。

拟合数据

grid_search.fit(X_train, y_train)

现在找到最佳参数。

grid_search.best_params_

grid_search.best_params_ 将在适合 X_train 和 y_train 后工作。

AttributeError: 'GridSearchCV' object has no attribute 'best_params_'

AttributeError: 'GridSearchCV' object has no attribute 'best_params_'

python

scikit-learn

grid-search

gridsearchcv