scikit-learn - AttributeError：“RandomizedSearchCV”对象没有属性“grid_scores_”

Question

当我尝试这段代码时：

import sklearn_crfsuite
from sklearn.model_selection import RandomizedSearchCV

f1_scorer = make_scorer(metrics.flat_f1_score,
                    average='weighted', labels=labels)
params_space = {
 'c1': scipy.stats.expon(scale=0.5),
 'c2': scipy.stats.expon(scale=0.05),
}

crf = sklearn_crfsuite.CRF(
    algorithm='lbfgs',
    max_iterations=100,
    all_possible_transitions=True)

rs = RandomizedSearchCV(crf, params_space,
                    cv=3,
                    verbose=1,
                    n_jobs=-1,
                    n_iter=50,
                    scoring=f1_scorer)

rs.fit(X_train, y_train)

_x = [s.parameters['c1'] for s in rs.grid_scores_]
_y = [s.parameters['c2'] for s in rs.grid_scores_]
_c = [s.mean_validation_score for s in rs.grid_scores_]

我收到错误：

AttributeError：“RandomizedSearchCV”对象没有属性“grid_scores_”

sklearn-crfsuite 版本 = 0.3.6

Answer 1

grid_scores_已弃用，cv_results_现在正在使用。

更多参考RandomizedSearchCV

Answer 2

cv_results_ 的实现方式与 grid_scores_ 不同

要提取正确的 _x、_y 和 _c 集，下面的代码应该可以工作

_x = [s['c1'] for s in rs.cv_results_['params']]
_y = [s['c2'] for s in rs.cv_results_['params']]
_c = [s for s in rs.cv_results_['mean_train_score']]