This is a tiny toolkit for performing training of maximum entropy models. It is a generic toolkit, which is applicable to conditional maximum entropy models. A special feature of this program is that it is written only in 132 lines of code (can be printed on one sheet of paper …). It includes training of model parameters, evaluation, perplexity and error rate computation, count-based feature reduction, Gaussian priors, feature count normalization. In addition, it is easy to use and efficient enough to deal with millions of features.
YASMET is free software under the GNU Public License and is distributed without any warranty.
If you find YASMET useful in your work, please cite this page.
Here it is: source code, gcc 3.x compatiple source code, (incomplete) documentation, little tutorial written by Deepak Ravichandran
Feature selection can be done with yasmetFS from Deepak Ravichandran.