Ramp Loss Linear Programming Nonparallel Support Vector Machine

被引：3

作者：

Liu, Dalian ^{[1
,2
]}

Chen, Dandan ^{[3
,4
]}

Shi, Yong ^{[1
,4
,5
,6
]}

Tian, Yingjie ^{[4
,5
]}

机构：

[1] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China

[2] Beijing Union Univ, Dept Basic Course Teaching, Beijing 100101, Peoples R China

[3] Univ Chinese Acad Sci, Coll Math Sci, Beijing 100049, Peoples R China

[4] Univ Chinese Acad Sci, Res Ctr Fictitious Econ & Data Sci, Beijing 100190, Peoples R China

[5] Univ Chinese Acad Sci, Key Lab Big Data Min & Knowledge Management, Beijing 100190, Peoples R China

[6] Univ Nebraska, Coll Informat Sci & Technol, Omaha, NE 68182 USA

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE 2016 (ICCS 2016) | 2016年 / 80卷

基金：

北京市自然科学基金; 中国国家自然科学基金;

关键词：

support vector machine; nonparallel; CCCP; linear programming; ramp loss;

D O I：

10.1016/j.procs.2016.05.432

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Motivated by the fact that the l(1)-penalty is piecewise linear, we proposed a ramp loss linear programming nonparallel support vector machine (ramp-LPNPSVM.), in which the l(1)-penalty is applied for the RNPSVM, for binary classification. Since the ramp loss has the piecewise linearity as well, ramp-LPNPSVM. is a piecewise linear minimization problem and a local minimum can be effectively found by the Concave Convex Procedure and experimental results on benchmark datasets confirm the effectiveness of the proposed algorithm. Moreover, the l(1)-penalty can enhance the sparsity.

引用

页码：1745 / 1754

页数：10

共 50 条

[31] Nonparallel Hyperplane Support Vector Machine for PU Learning
Zhang, Ying
Ju, XuChan
Tian, YingJie
2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014, : 703 - 708
[32] Structural nonparallel support vector machine for pattern recognition
Chen, Dandan
Tian, Yingjie
Liu, Xiaohui
PATTERN RECOGNITION, 2016, 60 : 296 - 305
[33] Nonparallel least square support vector machine for classification
Jiang Zhao
Zhiji Yang
Yitian Xu
Applied Intelligence, 2016, 45 : 1119 - 1128
[34] Training robust support vector machine with smooth Ramp loss in the primal space
Wang, Lei
Jia, Huading
Li, Jie
NEUROCOMPUTING, 2008, 71 (13-15) : 3020 - 3025
[35] Tightening big Ms in integer programming formulations for support vector machines with ramp loss
Baldomero-Naranjo, Marta
Martinez-Merino, Luisa, I
Rodriguez-Chia, Antonio M.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2020, 286 (01) : 84 - 100
[36] Discriminative information-based nonparallel support vector machine
Hou, Qiuling
Zhang, Jinxin
Liu, Liming
Wang, Yiju
Jing, Ling
SIGNAL PROCESSING, 2019, 162 : 169 - 179
[37] Nonparallel hyperplane support vector machine for binary classification problems
Shao, Yuan-Hai
Chen, Wei-Jie
Deng, Nai-Yang
INFORMATION SCIENCES, 2014, 263 : 22 - 35
[38] Active Learning with Nonparallel Support Vector Machine for Binary Classification
Zhao, Xi
Chen, Zhensong
Shi, Yong
2014 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW), 2014, : 101 - 104
[39] A novel projection nonparallel support vector machine for pattern classification
Hou, Qiuling
Liu, Liming
Zhen, Ling
Jing, Ling
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 75 : 64 - 75
[40] A multi-kernel framework with nonparallel support vector machine
Tang, Jingjing
Tian, Yingjie
NEUROCOMPUTING, 2017, 266 : 226 - 238

← 1 2 3 4 5 →