GridSearchCV没有属性grid.grid_scores_
GridSearchCV没有属性grid.grid_scores_
提问于 2019-04-05 16:26:07
尝试过的grid.cv_results_没有纠正问题
from sklearn.model_selection
import GridSearchCV
params = {
'decisiontreeclassifier__max_depth': [1, 2],
'pipeline-1__clf__C': [0.001, 0.1, 100.0]
}
grid = GridSearchCV(estimator = mv_clf,
param_grid = params,
cv = 10,
scoring = 'roc_auc')
grid.fit(X_train, y_train)
for params, mean_score, scores in grid.grid_scores_:
print("%0.3f+/-%0.2f %r" %
(mean_score, scores.std() / 2, params))
#AttributeError: 'GridSearchCV' object has no attribute 'grid_scores_'尝试用grid.grid_scores_代替grid.cv_results_，目的是打印不同的超参数值组合和通过10倍交叉验证计算的平均ROC分数。
from sklearn.model_selection
import GridSearchCV
params = {
'decisiontreeclassifier__max_depth': [1, 2],
'pipeline-1__clf__C': [0.001, 0.1, 100.0]
}
grid = GridSearchCV(estimator = mv_clf,
param_grid = params,
cv = 10,
scoring = 'roc_auc')
grid.fit(X_train, y_train)
for params, mean_score, scores in grid.grid_scores_:
print("%0.3f+/-%0.2f %r" %
(mean_score, scores.std() / 2, params))
#AttributeError: 'GridSearchCV' object has no attribute 'grid_scores_'回答 1
Stack Overflow用户
发布于 2019-11-15 13:03:01
在最新的scitkit learn libaray中，grid_scores_已经贬值，取而代之的是cv_results_。
cv_results_给出了网格搜索运行的详细结果。
grid.cv_results_.keys()
Output: dict_keys(['mean_fit_time', 'std_fit_time', 'mean_score_time', 'std_score_time', 'param_n_estimators', 'params', 'split0_test_score',
'split1_test_score', 'split2_test_score', 'split3_test_score', 'split4_test_score',
'mean_test_score', 'std_test_score', 'rank_test_score'])cv_results_给出了比grid_score更详细的输出。结果输出以字典的形式出现。通过遍历字典的关键字，可以从字典中提取相关的度量。下面是运行网格-搜索cv=5的示例
for i in ['mean_test_score', 'std_test_score', 'param_n_estimators']:
print(i," : ",grid.cv_results_[i])
Output: mean_test_score : [0.833 0.83 0.83 0.837 0.838 0.8381 0.83]
std_test_score : [0.011 0.009 0.010 0.0106 0.010 0.0102 0.0099]
param_n_estimators : [20 30 40 50 60 70 80]页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/55539770
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