Unsupervised clustering based reduced support vector machines

被引：0

作者：

Zheng, SF ^{[1
]}

Lu, XF ^{[1
]}

Zheng, NN ^{[1
]}

Xu, WP ^{[1
]}

机构：

[1] Xian Jiaotong Univ, Inst Artificial Intelligence & Robot, Xian 710049, Peoples R China

来源：

2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL II, PROCEEDINGS: SPEECH II; INDUSTRY TECHNOLOGY TRACKS; DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS; NEURAL NETWORKS FOR SIGNAL PROCESSING | 2003年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

To overcome the vast computation of the standard support vector machines (SVMs), Lee and Mangasarian proposed reduced support vector machines (RSVM). But they select 'support vectors' randomly from the training set, and this will affect the test result. In this paper, we select some representative vectors as support vectors via a simple unsupervised clustering algorithm, and then apply the RSVM method on these vectors. The proposed method can get higher recognition accuracy with fewer support vectors compared to the original RSVM, with the advantage of reducing the running time significantly.

引用

页码：821 / 824

页数：4

共 50 条

[41] Wavelet Frame Accelerated Reduced Support Vector Machines
Ratsch, Matthias
Teschke, Gerd
Romdhani, Sami
Vetter, Thomas
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2008, 17 (12) : 2456 - 2464
[42] Variant Methods of Reduced Set Selection for Reduced Support Vector Machines
Chien, Li-Jen
Chang, Chien-Chung
Lee, Yuh-Jye
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2010, 26 (01) : 183 - 196
[43] Robust Unsupervised Lagrangian Support Vector Machines for Supply Chain Management
Zhao, Kun
Liu, Yong-sheng
Deng, Nai-yang
CUTTING-EDGE RESEARCH TOPICS ON MULTIPLE CRITERIA DECISION MAKING, PROCEEDINGS, 2009, 35 : 649 - +
[44] An idea of a clustering algorithm using support vector machines based on binary decision tree
Elaidi, Halima
Elhaddar, Younes
Benabbou, Zahra
Abbar, Hassan
2018 INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND COMPUTER VISION (ISCV2018), 2018,
[45] Unsupervised Parameter Estimation for One-Class Support Vector Machines
Ghafoori, Zahra
Rajasegarar, Sutharshan
Erfani, Sarah M.
Karunasekera, Shanika
Leckie, Christopher A.
ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2016, PT II, 2016, 9652 : 183 - 195
[46] Unsupervised spatiotemporal fMRI data analysis using support vector machines
Song, Xiaomu
Wyrwicz, Alice M.
NEUROIMAGE, 2009, 47 (01) : 204 - 212
[47] Support Vector Machines Based on Sectional Set Fuzzy K-Means Clustering
Ma, Li-juan
Ha, Ming-hu
FUZZY INFORMATION AND ENGINEERING, VOL 1, 2009, 54 : 420 - 425
[48] Facial complex expression recognition based on fuzzy kernel clustering and support vector machines
Zhao, Hui
Wang, Zhiliang
Men, Jihui
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 1, PROCEEDINGS, 2007, : 562 - +
[49] A Kernel Clustering Algorithm for Fast Training of Support Vector Machines
刘笑嶂
冯国灿
JournalofDonghuaUniversity(EnglishEdition), 2011, 28 (01) : 53 - 56
[50] Fuzzy neural modeling via clustering and support vector machines
Tovar, Julio Cesar
Yu, Wen
PROCEEDINGS OF THE 2007 IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1-3, 2007, : 723 - 728

← 1 2 3 4 5 →