scikit-learn 中的“详细"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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