To R or not to R

At the moment 90% of the research in our lab is done using Matlab. Some of us have tried Python but were dissapointed by how hard it was to get decent (read: native) numerical routines on par with Matlab. I’ve been developing on the .NET platform with a little bit of Java development (for Amazon’s Elastic Map-Reduce) on the side. We’ve had a few discussions in our lab recently about switching to R for our machine learning research. A decision hasn’t been made and we’re wondering what the larger machine learning community thinks about this issue. Here’s a list of pros and cons that I’ve come up with

Pros:

• great support for statistical functions
• great support from the statistical community
• good (if not better) plotting that Matlab
• reasonable fast (check out Dave’s benchmarking)
• free (very important!) if we want to run a job on 100 machines (e.g. in the cloud), I believe currently you need a matlab licence for each one

Cons:

• pre-historic interface, doesn’t compare to modern IDE’s
• debugging doesn’t seem up to Matlab standards
• not much support in machine learning community (?)
• learning curve

The jury is still out on this one … I really wonder how many machine learners out there already use R?