12 August 2009

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


  • 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


  • 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?