HLearn: A Machine Learning Library for Haskell (2013) [pdf] • Hacker News Board

Re: HLearn: A Machine Learning Library for Haskell (2013) [pdf]

#21

Post by jackpirate » Wed, May 24, 2017, 10:37 PM UTC

readpunch wrote: post #16

jackpirate wrote: post #8

Hi everyone, author of HLearn here :) This is a bit awkward for me as I've paused the development of HLearn and emphatically do not recommend anyone use it. The main problem is that Haskell (which I otherwise love) has poor support for numerical computing. I've tried developing an alternative standard library to improve the situation ( https://github.com/mikeizbicki/subhask ), but Haskell's type system isn't yet powe…

I am learning Haskell. Can you explain why you think Haskell has poor support for numerical computing?

See bos's comment above. It's mostly just poor relative to what I wish it had. You can see the subhask library for a small taste of what I wish it had.

Re: HLearn: A Machine Learning Library for Haskell (2013) [pdf]

#22

Post by jackpirate » Wed, May 24, 2017, 10:41 PM UTC

bjz_ wrote: post #12

jackpirate wrote: post #8

Hi everyone, author of HLearn here :) This is a bit awkward for me as I've paused the development of HLearn and emphatically do not recommend anyone use it. The main problem is that Haskell (which I otherwise love) has poor support for numerical computing. I've tried developing an alternative standard library to improve the situation ( https://github.com/mikeizbicki/subhask ), but Haskell's type system isn't yet powe…

> Haskell's type system isn't yet powerful enough to do what I want. What still needs to be done? Does Idris have enough of the power that you need?

I've not used Idris too much, so I can't say for sure. My guess is that the answer is that it could do everything I want type-system-wise, but there are things I want outside of the type sytem that I don't think it could do.

For example, I want the compiler to automatically rewrite my code to be much more efficient and numerically stable (see the HerbiePlugin to the GHC compiler which goes this https://github.com/mikeizbicki/HerbiePlugin). My understanding is that the Idris compiler gets much less engineering work done on it (outside of the type system), and so getting efficient running code will be too difficult.

Re: HLearn: A Machine Learning Library for Haskell (2013) [pdf]

#23

Post by YeGoblynQueenne » Thu, May 25, 2017, 3:48 PM UTC

jackpirate wrote: post #8

Hi everyone, author of HLearn here :) This is a bit awkward for me as I've paused the development of HLearn and emphatically do not recommend anyone use it. The main problem is that Haskell (which I otherwise love) has poor support for numerical computing. I've tried developing an alternative standard library to improve the situation ( https://github.com/mikeizbicki/subhask ), but Haskell's type system isn't yet powe…

That's kind of sad that you've given up on this project. I visited this thread to comment that I'm working on a similar project, but for Swi-Prolog (a statistical NLP module - it's my own initiative and about a month away from sharing with the world).

I think it's a big shame that traditional AI and computer-sciency languages like Haskell and Prolog have lagged so far behind the mainstream ones in terms of machine learning and as machine learning gets more popular I'm worried this will cause them to fall by the wayside even more than they have already.

What is it that's making Haskell bad at numerical computing? I would have thought it's not much worse than e.g. Julia or Python but even if it is, I always figured there's other benefits to programming in Haskell- otherwise we'd all be geeking over FORTRAN, I guess.

With Prolog the big issue is that statistical AI algorithms tend to go a lot faster with mutable, indexable data structures and those don't have a lot of support in Prolog. What is it that's really bothering you with Haskell? Could you give an example?

[Note: I'm a Haskell noob, but I should be able to handle code examples]