scikit-learn中的"verbose"参数 [英] 'verbose' argument in scikit-learn

问题描述

许多scikit-learn函数都有一个verbose参数，根据其文档，"[c]控制详细程度:消息越高，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吗?)，以及哪些详细程度对应于哪些整数.我在文档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，哪个整数映射到详细程度?

推荐答案

如文档字符串所述，较高的整数对应较高的详细程度.您可以设置verbosity = 100，但我敢肯定它会与verbosity = 10一样.如果要查找每个整数的每个估计量准确打印的列表，则必须查看源. 我认为大多数估算者的详细程度只有两个或三个，我认为3或更高级别是最详细的.

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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