Please use this identifier to cite or link to this item:
|Title:||A simple and efficient algorithm for gene selection using sparse logistic regression|
|Source:||Shevade, S.K., Keerthi, S.S. (2003-11-22). A simple and efficient algorithm for gene selection using sparse logistic regression. Bioinformatics 19 (17) : 2246-2253. ScholarBank@NUS Repository. https://doi.org/bioinformatics/btg308|
|Abstract:||Motivation: This paper gives a new and efficient algorithm for the sparse logistic regression problem. The proposed algorithm is based on the Gauss-Seidel method and is asymptotically convergent. It is simple and extremely easy to implement; it neither uses any sophisticated mathematical programming software nor needs any matrix operations. It can be applied to a variety of real-world problems like identifying marker genes and building a classifier in the context of cancer diagnosis using microarray data. Results: The gene selection method suggested in this paper is demonstrated on two real-world data sets and the results were found to be consistent with the literature.|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
WEB OF SCIENCETM
checked on Nov 18, 2017
checked on Jan 14, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.