Discrete Component Analysis
统计理论
2007-06-13 v1 统计理论
摘要
This article presents a unified theory for analysis of components in discrete data, and compares the methods with techniques such as independent component analysis, non-negative matrix factorisation and latent Dirichlet allocation. The main families of algorithms discussed are a variational approximation, Gibbs sampling, and Rao-Blackwellised Gibbs sampling. Applications are presented for voting records from the United States Senate for 2003, and for the Reuters-21578 newswire collection.
引用
@article{arxiv.math/0604410,
title = {Discrete Component Analysis},
author = {Wray Buntine and Aleks Jakulin},
journal= {arXiv preprint arXiv:math/0604410},
year = {2007}
}