Genetic Support Vector Classification and Feature Selection

被引：1

作者：

Mejia-Guevaara, Ivan ^{[1
]}

Kuri-Morales, Angel ^{[2
]}

机构：

[1] Univ Nacl Autonoma Mexico, Inst Invest Matemat Aplicadas & Sistemas, Circuito Escolar S-N,CU, Mexico City 04510, DF, Mexico

[2] Inst Tecnol Autonoma Mexico, Dept Comp, Mexico City, DF, Mexico

来源：

PROCEEDINGS OF THE SPECIAL SESSION OF THE SEVENTH MEXICAN INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE - MICAI 2008 | 2008年

关键词：

D O I：

10.1109/MICAI.2008.48

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An important issue regarding the design of Support Vector Machines (SVMs) is considered in this article, namely, the fine tuning of parameters in SVMs. This problem is tackled by using a self-adaptive Genetic Algorithm (GA). The same GA is used for feature selection. We validate our results implementing some statistical tests based on single domain benchmark-data set, which are used for comparison with other traditional methods. One of these methods is commonly used for the selection of parameters in SVMs.

引用

页码：75 / +

页数：3

共 50 条

[21] Automatic feature scaling and selection for support vector machine classification with functional data
Asunción Jiménez-Cordero
Sebastián Maldonado
Applied Intelligence, 2021, 51 : 161 - 184
[22] Sensitivity of Support Vector Machines to Random Feature Selection in Classification of Hyperspectral Data
Waske, Bjoern
van der Linden, Sebastian
Benediktsson, Jon Atli
Rabe, Andreas
Hostert, Patrick
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2010, 48 (07): : 2880 - 2889
[23] Enzyme classification using multiclass support vector machine and feature subset selection
Pradhan, Debasmita
Padhy, Sudarsan
Sahoo, Biswajit
COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2017, 70 : 211 - 219
[24] Geographical Classification of Tannat Wines Based on Support Vector Machines and Feature Selection
Costa, Nattane Luiza
Garcia Llobodanin, Laura Andrea
Castro, Inar Alves
Barbosa, Rommel
BEVERAGES, 2018, 4 (04):
[25] Feature selection and classification of breast cancer diagnosis based on support vector machines
Purnami, Santi Wulan
Rahayu, S. P.
Embong, Abdullah
INTERNATIONAL SYMPOSIUM OF INFORMATION TECHNOLOGY 2008, VOLS 1-4, PROCEEDINGS: COGNITIVE INFORMATICS: BRIDGING NATURAL AND ARTIFICIAL KNOWLEDGE, 2008, : 500 - 505
[26] Multi-View Scaling Support Vector Machines for Classification and Feature Selection
Xu, Jinglin
Han, Junwei
Nie, Feiping
Li, Xuelong
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2020, 32 (07) : 1419 - 1430
[27] Automatic feature scaling and selection for support vector machine classification with functional data
Jimenez-Cordero, Asuncion
Maldonado, Sebastian
APPLIED INTELLIGENCE, 2021, 51 (01) : 161 - 184
[28] High dimensional data classification and feature selection using support vector machines
Ghaddar, Bissan
Naoum-Sawaya, Joe
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2018, 265 (03) : 993 - 1004
[29] NONPARAMETRIC FEATURE SELECTION AND SUPPORT VECTOR MACHINE FOR POLARIMETRIC SAR DATA CLASSIFICATION
Maghsoudi, Yasser
Collins, Michael
Leckie, Donald G.
2011 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2011, : 2857 - 2860
[30] Feature Selection of Corn Seed Based on Genetic Algorithm and Support Vector Machine
Cheng Hong
Pang Li Xin
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON INFORMATIONIZATION, AUTOMATION AND ELECTRIFICATION IN AGRICULTURE, 2008, : 494 - 499

← 1 2 3 4 5 →