Questions about Mahout's maturity

[Glenn Murray]

Hi,

Is Mahout ready for prime time? A quick glance at the site shows that some algorithms seem to be implemented, but many not (e.g., boosting, support vector machines, neural nets). My hope would be that Mahout could provide a way to quickly apply a variety of algorithms for comparison.

A secondary question is how much theory is in this book? Is there some attempt to cover some basic notions and formulas?

Thanks,
Glenn

[Sean Owen]

(Those are fairly different types of algorithms.) I do not know that you'll see a lot more different types of algorithms implemented, soon, though that's bound to come over time. I sense that what you see now is what you'll see in a year, except that it will be more refined.

But that's somewhat different from the question of being ready to use. If you need algorithm X and it's not implemented, no, it's not ready for you to use. But if you need Y and you find Y in the project -- I would encourage you to try it. I think any of it is ready enough to try in production, and some bits have been quite battle-tested. It really depends on what you're using.

[Ted Dunning]

I would definitely second what Sean says. What we have in Mahout is a collection of algorithms that we know will scale. Mahout is not about being the broadest collection of learning algorithms. It is about having scalable algorithms that are reliable in scaling situations.

If you want a broad selection of algorithms with much less attention paid to scalability and deployability, then use R.

If you think we really, really need some algorithm in Mahout and you know how it should be implemented to be scalable, please do come over to [email protected] and let's talk about it!