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Is there an (un)official overview of sklearn hyper-parameters to tune for each model? I find myself often having to google extensively before getting an exhaustive list for any given model.

Alternatively, are there non-sklearn guides or cheat sheets which cover most standard algorithms?

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If you already know the hyperparameters that you want to tune, of course there is the quite extensive scikitlearn documentation ( http://scikit-learn.org/stable/user_guide.html ).

If you want an overview of hyperparameters that would be most useful to tune, I would advise you to have a look at the library of the caret R package. It is an R package, but it has very extensive documentation on tuning hyperparameters and when you know which hyperparameters you want to tune you can just look them up on scikitlearn documentation ( https://topepo.github.io/caret/available-models.html ).

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  • $\begingroup$ Thanks this is exactly what I was looking for! I will leave the question open a bit longer for potential sklearn specific lists, but this is a great alternative indeed. $\endgroup$
    – ciri
    Oct 13, 2018 at 9:40

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