Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in embedded methods the features selection part can not be separated from the learning part. Existing embedded methods are reviewed based on a unifying mathematical framework.
| Author(s): | Lal, TN. and Chapelle, O. and Weston, J. and Elisseeff, A. |
| Book Title: | Feature Extraction: Foundations and Applications |
| Pages: | 137-165 |
| Year: | 2006 |
| Day: | 0 |
| Series: | Studies in Fuzziness and Soft Computing ; 207 |
| Editors: | Guyon, I. , S. Gunn, M. Nikravesh, L. A. Zadeh |
| Publisher: | Springer |
| Bibtex Type: | Book Chapter (inbook) |
| Address: | Berlin, Germany |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Language: | en |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
| Links: | |
BibTex
@inbook{3012,
title = {Embedded methods},
booktitle = {Feature Extraction: Foundations and Applications},
abstract = {Embedded methods are a relatively new approach to feature selection. Unlike filter methods, which do not incorporate learning, and wrapper approaches, which can be used with arbitrary classifiers, in embedded methods the features selection part can not be separated from the learning part.
Existing embedded methods are reviewed based on a unifying mathematical framework.},
pages = {137-165},
series = {Studies in Fuzziness and Soft Computing ; 207},
editors = {Guyon, I. , S. Gunn, M. Nikravesh, L. A. Zadeh},
publisher = {Springer},
organization = {Max-Planck-Gesellschaft},
school = {Biologische Kybernetik},
address = {Berlin, Germany},
year = {2006},
slug = {3012},
author = {Lal, TN. and Chapelle, O. and Weston, J. and Elisseeff, A.}
}