Sklearn RandomizedSearchCV突然卡住了

时间:2017-10-06 04:28:42

标签: performance parameters scikit-learn grid-search

我尝试为SVM模型做一个RandomizedSearchCV,但它似乎需要永远。它适用于KNN。在完成某些任务后,我发现该过程停留在某处。以下是我的代码:

# SVC Parameter Tuning
svc_params = {'C': np.power(10, np.arange(-5., 1.)), 
              'kernel': ['rbf', 'linear', 'sigmoid', 'poly'],
              'degree': np.arange(3, 21), 
              'coef0' : np.linspace(0, 1, 100), 
              'shrinking': [True, False], 
              'class_weight' : ['balanced', None]}

svc = RandomizedSearchCV(SVC(), 
                         svc_params, 
                         cv = 5, 
                         scoring = 'roc_auc', 
                         n_jobs = 128, 
                         n_iter = 100,
                         verbose = 2)
经过一些结果后,这个过程陷入了困境。

[CV]  kernel=poly, C=0.0001, degree=20, coef0=0.848484848485, 
shrinking=True, class_weight=balanced, total=  11.1s
[CV]  kernel=poly, C=0.0001, degree=20, coef0=0.848484848485, 
shrinking=True, class_weight=balanced, total=  11.0s
[CV]  kernel=poly, C=0.0001, degree=20, coef0=0.848484848485, 
shrinking=True, class_weight=balanced, total=  11.5s

我真的没有线索。谢谢你的帮助!

0 个答案:

没有答案