Feature selection for SVMs

被引：0

作者：

Weston, J ^{[1
]}

Mukherjee, S ^{[1
]}

Chapelle, O ^{[1
]}

Pontil, M ^{[1
]}

Poggio, T ^{[1
]}

Vapnik, V ^{[1
]}

机构：

[1] Barnhill BioInformat com, Savannah, GA 31406 USA

来源：

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 13 | 2001年 / 13卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We introduce a method of feature selection for Support Vector Machines. The method is based upon finding those features which minimize bounds on the leave-one-out error. This search can be efficiently performed via gradient descent. The resulting algorithms are shown to be superior to some standard feature selection algorithms on both toy data and real-life problems of face recognition, pedestrian detection and analyzing DNA microarray data.

引用

页码：668 / 674

页数：7

共 50 条

[1] An Accurate, Fast Embedded Feature Selection for SVMs
Hamed, Tarfa
Dara, Rozita
Kremer, Stefan C.
[J]. 2014 13TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA), 2014, : 135 - 140
[2] Cascaded feature selection in SVMs text categorization
Masuyama, T
Nakagawa, H
[J]. COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, PROCEEDINGS, 2003, 2588 : 588 - 591
[3] Evaluating feature selection for SVMs in high dimensions
Nilsson, Roland
Pena, Jose M.
Bjoerkegren, Johan
Tegner, Jesper
[J]. MACHINE LEARNING: ECML 2006, PROCEEDINGS, 2006, 4212 : 719 - 726
[4] Feature selection algorithms to reduce processing time in classification with SVMs
Toledo-Perez D C
Rodriguez-Resendiz J
Gomez-Loenzo R A
Martinez-Trinidad J F
Carrasco-Ochoa J A
[J]. 2021 XVII INTERNATIONAL ENGINEERING CONGRESS (CONIIN), 2021,
[5] Feature selection in MLPs and SVMs based on maximum output information
Sindhwani, V
Rakshit, S
Deodhare, D
Erdogmus, D
Principe, JC
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 2004, 15 (04): : 937 - 948
[6] Classification of brain glioma by using SVMs bagging with feature selection
Li, Guo-Zheng
Liu, Tian-Yu
Cheng, Victor S.
[J]. DATA MINING FOR BIOMEDICAL APPLICATIONS, PROCEEDINGS, 2006, 3916 : 124 - 130
[7] Facial feature selection based on SVMs by regularized risk minimization
Li, Weihong
Gong, Weiguo
Yang, Liping
Chen, Weimin
Gu, Xiaohua
[J]. 18TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 3, PROCEEDINGS, 2006, : 540 - +
[8] SVMs ensemble for radar target recognition based on evolutionary feature selection
Zhang, Xiangrong
Jiao, Licheng
Gou, Shuiping
[J]. 2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 2804 - 2808
[9] Genetic Evolution-Based Feature Selection for Software Defect Prediction Using SVMs
Goyal, Somya
[J]. JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2022, 31 (11)
[10] Feature selection for multi-class underwater acoustic targets via SVMs and genetic algorithms
Yang, HH
Sun, JC
[J]. PROGRESS IN INTELLIGENCE COMPUTATION & APPLICATIONS, 2005, : 397 - 401

← 1 2 3 4 5 →