问题描述
许多 scikit-learn 函数都有一个 verbose
参数,根据他们的文档,[c] 控制冗长:越高,消息越多";(例如,GridSearchCV).
Many scikit-learn functions have a verbose
argument that, according to their documentation, "[c]ontrols the verbosity: the higher, the more messages" (e.g., GridSearchCV).
不幸的是,没有提供关于允许使用哪些整数的指南(例如,用户可以将详细程度设置为 100?)以及什么级别的详细程度对应于哪些整数.我在文档中的任何地方都找不到此信息.
Unfortunately, no guidance is provided on which integers are allowed (e.g., can a user set verbosity to 100?) and what level of verbosity corresponds to which integers. I cannot find this information anywhere in the documentation.
我的问题是,哪些整数映射到哪个级别的详细程度?
推荐答案
正如文档字符串所说,更高的整数映射到更高的详细程度.您可以设置verbosity=100,但我很确定它与verbosity=10 相同.如果您正在寻找为每个整数的每个估计器打印的确切内容的列表,则必须查看源.我认为大多数估算器只有两到三个级别的详细程度,我认为 3 或以上将是您可以获得的最详细的程度.
Higher integers map to higher verbosity as the docstring says. You can set verbosity=100 but I'm pretty sure it will be the same as verbosity=10. If you are looking for a list of what exactly is printed for each estimator for each integer, you have to look into the source.I think most estimators only have two or three levels of verbosity, I think 3 or above will be the most verbose you can get.
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