Machine learning libraries for Ruby

Question

Are there any machine learning libraries for Ruby that are relatively complete (including a wide variety of algorithms for supervised and unsupervised learning), robustly tested, and well-documented? I love Python's scikit-learn for its incredible documentation, but a client would prefer to write the code in Ruby since that's what they're familiar with.

Ideally I am looking for a library or set of libraries which, like scikit and numpy, can implement a wide variety of data structures like sparse matrices, as well as learners.

Some examples of things we'll need to do are binary classification using SVMs, and implementing bag of words models which we hope to concatenate with arbitrary numeric data, as described in this StackOverflow post.

Answer 1

I'll go ahead and post an answer for now; if someone has something better I'll accept theirs.

At this point the most powerful option appears to be accessing WEKA using jRuby. We spent yesterday scouring the 'net, and this combination was even used by a talk at RailsConf 2012, so I would guess if there were a comparable pure ruby package, they would have used it.

Note that if you know exactly what you need, there are plenty of individual libraries that either wrap standalone packages like libsvm or re-implement some individual algorithms like Naive Bayes in pure Ruby and will spare you from using jRuby.

But for a general-purpose library, WEKA and jRuby seem to be the best bet at this time.