试过 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_'
尝试替换grid.grid_scores_
为grid.cv_results_
目标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 AUC 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_'