I agree with the author that it would be better to have unregularized logistic regression as the default. This has tripped me up in the past, but luckily sklear

I agree with the author that it would be better to have unregularized logistic regression as the default. This has tripped me up in the past, but luckily sklearn docs are good so I could figure out what’s going on. Random forest defaults are clearly wrong. n_trees are set to 10 which just doesn’t work as well as a reasonable default like 100. I just checked the docs and it looks like they are updating it in a future version. I think this wouldn’t be a problem, but there is so much hype around data science, boot camp grads with only a high level understanding of ML, etc. it probably makes sense to make the library as idiot proof as possible with the default Params. Either way I don’t care much, it’s still an awesome lib for free and nuances like this don’t affect me