# Is CV the right site for this question?

I just asked the following question:

What are attention mechanism exactly?

It seems that attention-related questions haven't received answers on this site. Is this the right site for these questions? After Data Science, I found another site which seems related to Deep Learning questions: Artificial Intelligence (and I hope there isn't a third one). I believe Cross Validated is the most suitable site for this kind of questions, but I would like to have your confirmation.

• It seems to pertain to ANNs, which are on topic. I would say it's OK. We can see how it fares. In the interim, you added the [attention] tag, but it has no excerpt. Can you provide one? May 4 '18 at 19:03
• Hi @gung, I didn't create the [attention] label, I just used it because the site auto-completion suggested it (I did notice that it didn't have an excerpt, which I found odd). Given that I've never really understood what attention mechanism are (that's why I'm asking), I don't feel qualified to write an excerpt. If no one else volunteers to write a proper excerpt, I can surely parrot back the sentences commonly used to describe attention, but I'm not sure I'll make the community a great service. May 5 '18 at 10:42
• FWIW the tag was created by @FranckDernoncourt. May 5 '18 at 12:17
• Sorry for not having written an excerpt when creating the tag :-) May 17 '18 at 4:42

It's on-topic here because it is about machine learning, and machine learning is squarely on-topic here.

• Some folks have said "it is too software-side of machine learning" so it goes on stack-overflow. Some folks have said "its too pure-mathy" so it goes on mathematics or data science. Some have said "its too academia" or "its too work-professionalism" so I had to move to those forums. There is no perfect Venn diagram as to which parts of stack-exchange it goes on, but it can go on one of them. May 10 '18 at 18:28
• @EngrStudent those folks are wrong. StackExchange does not have the philosophy "It's not offtopic here only because it's better suited elsewhere". If something is on-topic on both A and B, OP can decide where to post, but only pick one. May 15 '18 at 12:14
• Try this: stats.stackexchange.com/review/close/186430 Since when isn't using a neural network to forecast time-series data on-topic? May 17 '18 at 14:19
– Sycorax Mod
May 17 '18 at 14:32
• I was just supplying one of several examples where just because something is "machine learning" or otherwise "core" to stats, it gets voted as "off-topic" for the stats forum. Goes along with the first topic. fwiw, I love your answer, and I want these sorts of things to be on-topic. I've just been axed and seen things axed that depart from the ideal. May 17 '18 at 14:55
• @EngrStudent Just speculating, but when the title includes "how to do ... in R," people tend to regard that as off-topic because the question asks for explanation of how to use software -- that is, the answer is code and/or software documentation. On the other hand, if the question asked for the predictive equations for a specific model, it would probably be on-topic -- the answer is about machine learning as a mathematical discipline, not software engineering.
– Sycorax Mod
May 17 '18 at 14:58