On an Application of Relative Entropy
Statistical Mechanics
2007-05-23 v2 Disordered Systems and Neural Networks
Abstract
We describe general approach to classification of character sequences (texts, DNA) using relative entropy estimated by off-the-shelf compression and Markov Chains and find them precise enough. We also notice that the method for estimating relative entropy described in the paper cond-mat/0108530 "Language Trees..." by D. Benedetto et al. was considered earlier and was found to be easily surpassed by the simple and computationally effective first order Markov Chain approach.
Cite
@article{arxiv.cond-mat/0205521,
title = {On an Application of Relative Entropy},
author = {Dmitry V. Khmelev and William J. Teahan},
journal= {arXiv preprint arXiv:cond-mat/0205521},
year = {2007}
}
Comments
1 page, to be published in PRL