Monday, November 3, 2008


I talked to a couple people at ISMIR about a new machine learning toolbox, called FASTLIB (although, it appears to be called both FASTLIB or MLPACK). This toolbox was developed by Alexander Gray's lab in the College of Computing at Georgia Tech and I used this extensively in Alexander Gray's class. I highly recommend that anyone try this toolbox for their machine learning needs. Programming within the guidelines greatly reduces the programming time (almost to the simplicity of MATLAB), while retaining computational speed and memory capacity. If you are like me, how have had to make the judgement call between programming something in MATLAB and having it run a long time, or spending a long time writing and debugging C++ code so that the algorithm runs quicker.

The official place to download the package seems to be here; however, I found some issues (expected with a version 1.0). The stripped down package on an old class website seemed easier to install. The individual built-in algorithms can be added manually later. I hope to have a small series of posts demonstrating the ease of programming style.

No comments: