[SciPy-dev] [ANN] pyem 0.4.1, a numpy module for Gaussian Mixture Models
david at ar.media.kyoto-u.ac.jp
Fri Jul 14 06:39:51 CDT 2006
a few weeks ago, I submitted a small module for Expectation
Maximization for Gaussian Mixture Models. I had the time recently to
improve it significantly, and I've just made available a second public
Example of training:
The major user-visible changes are the use of distutils for
packaging, and speed improvement for diagonal models. Now, on a pentium
M @ 1.2 Mhz, 10 iterations of EM takes around 6 seconds for a
20-dimension, diagonal model of 20 components with 10^4 points for
training, including the k-mean initialization (pyrex version). This
should make it usable for applications such as speaker recognition,
etc... More speed improvements (particularly full covariance matrices)
are to be expected once I managed to include my separate project which
implements the whole EM for GMM in C.
Examples are available in the module, and several parts of the
module can be executed directly to see some basic uses (including plotting).
I tried several tools which I am not very familiar with yet
(distutils, pyrex), so there may be some problems depending on the
configuration; I tested the package on linux x86 (ubuntu dapper), one
machine with and and one without pyrex.
As always, comments, suggestion, bugs reports are welcome,
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