Name
Title | ||
|---|---|---|
Maximum entropy and maximum likelihood criteria for feature selection from multivariate data |
Abstract | ||
|---|---|---|
We discuss several numerical methods for optimum feature selection for multivariate data based on maximum entropy and maximum likelihood criteria. Our point of view is to consider observed data x1, x2,..., xN in Rd to be samples from some unknown pdf P. We project this data onto d directions, subsequently estimate the pdf of the univariate data, then find the maximum entropy (or likelihood) of all multivariate pdfs in Rd with marginals in these directions prescribed by the estimated univariate pdfs and finally maximize the entropy (or likelihood) further over the choice of these directions. This strategy for optimal feature selection depends on the method used to estimate univariate data |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1109/ISCAS.2000.856048 | Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium |
Keywords | Field | DocType |
entropy,feature extraction,maximum likelihood estimation,maximum entropy,maximum likelihood criteria,multivariate data,observed data,optimal feature selection,pdf,univariate data,maximum likelihood,feature selection,speech recognition,entropy coding,speech processing | Maximum-entropy Markov model,Feature selection,Multivariate statistics,Expectation–maximization algorithm,Maximum likelihood,Principle of maximum entropy,Statistics,Maximum likelihood sequence estimation,Physics | Conference |
Volume | Issue | ISBN |
3 | 2 | 0-7803-5482-6 |
Citations | PageRank | References |
15 | 2.40 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sankar Basu | 1 | 168 | 32.17 |
| charles a micchelli | 2 | 47 | 7.73 |
| Peder A. Olsen | 3 | 398 | 37.80 |