# Can I ask questions about an R package for machine learning with unclear documentation?

Machine Learning (in general) is on topic (see: Are the "Machine Learning" questions on topic?).

I am working with the h2o package and the documentation is .. obtuse. It is hard to use and generally uninformative. I want to ask (and maybe answer) questions that document things like "here is the code to upload a text file to h2o from your interface" or "here is how you start the evaluation of data using a pre-loaded and pre-built rf/glm/gbm/dl/nn/... ".

Can you tell me if doing this is good or bad, or if I should ask these questions elsewhere, like in Stack Overflow?

• This post appears to have tailed off mid-sentence! (I've seen this happen to a couple of people before, and I wonder what causes it.) – Silverfish Feb 5 '15 at 1:59
• The generic advice at stats.stackexchange.com/help/on-topic on software-related questions seems to apply here. Else in what sense is that advice problematic or irrelevant? – Nick Cox Feb 5 '15 at 12:31
• It is the half-and-half world between programming (details of the language) and the fundamental idea behind the language - aka the Machine Learning part. The answer that I referenced seems to say a loud yes. The on-topic generic advice seems to say "get the heck out". I'm not sure which to listen to and if you want one then we as a community don't get the other. – EngrStudent Feb 5 '15 at 14:10
• Think there's a difference, though, between the examples from the answer you referenced - e.g. "Why does the kernelized support vector machine algorithm care that the kernel function be positive semi-definite? What happens if it isn't?" - & the examples you propose - e.g. "here is the code to upload a text file to h2o from your interface". The former don't sound at all like the "routine data processing" or "details of the language" referred to in the guide to what's on topic; the latter do. – Scortchi - Reinstate Monica Feb 5 '15 at 16:19

On the other hand, if you want to talk about "the evaluation of data", that is on-topic here, even if code is appended. There is certainly nothing wrong with having code (R, SAS, Stata, MATLAB, etc.) as part of a question or an answer. My opinion has always been that what is important is what the OP needs explained, regardless of how the question is phrased. If what the OP needs to know is about the machine learning, then it is best here, but if what they need to know is about the code, then it belongs on SO. (If they need both, then it could be either, but we can defer to the OP.)