Leave-one-out bounds for support vector regression model selection

被引：79

作者：

Chang, MW ^{[1
]}

Lin, CJ ^{[1
]}

机构：

[1] Natl Taiwan Univ, Dept Comp Sci & Informat Engn, Taipei 106, Taiwan

来源：

NEURAL COMPUTATION | 2005年 / 17卷 / 05期

关键词：

D O I：

10.1162/0899766053491869

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Minimizing bounds of leave-one-out errors is an important and efficient approach for support vector machine (SVM) model selection. Past research focuses on their use for classification but not regression. In this letter, we derive various leave-one-out bounds for support vector regression (SVR) and discuss the difference from those for classification. Experiments demonstrate that the proposed bounds are competitive with Bayesian SVR for parameter selection. We also discuss the differentiability of leave-one-out bounds.

引用

下载

页码：1188 / 1222

页数：35

共 50 条

[21] Efficient Leave-One-Out Strategy for Supervised Feature Selection
Feng, Dingcheng
Chen, Feng
Xu, Wenli
TSINGHUA SCIENCE AND TECHNOLOGY, 2013, 18 (06) : 629 - 635
[22] Efficient Leave-One-Out Strategy for Supervised Feature Selection
Dingcheng Feng
Feng Chen
Wenli Xu
Tsinghua Science and Technology, 2013, 18 (06) : 629 - 635
[23] Lower bounds for empirical and leave-one-out estimates of the generalization error
Gavin, G
Teytaud, O
IJCNN'01: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS, 2001, : 1238 - 1243
[24] Backward elimination model construction for regression and classification using leave-one-out criteria
Hong, X.
Mitchell, R. J.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2007, 38 (02) : 101 - 113
[25] Fast leave-one-out evaluation for dynamic gene selection
Z. Ying
K.C. Keong
Soft Computing, 2006, 10 : 346 - 350
[26] Leave-One-Out Cross-Validation Based Model Selection for Manifold Regularization
Yuan, Jin
Li, Yan-Ming
Liu, Cheng-Liang
Zha, Xuan F.
ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 1, PROCEEDINGS, 2010, 6063 : 457 - +
[27] Limitations of “Limitations of Bayesian Leave-one-out Cross-Validation for Model Selection”
Vehtari A.
Simpson D.P.
Yao Y.
Gelman A.
Computational Brain & Behavior, 2019, 2 (1) : 22 - 27
[28] Leave-one-out manifold regularization
Yuan, Jin
Liu, Xuemei
Liu, Cheng-Liang
EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (05) : 5317 - 5324
[29] Evolutionary selection of neural networks satisfying leave-one-out criteria
Nardinocchi, G
Jankowski, S
Balsi, M
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS IV, 2006, 6159
[30] Fault diagnosis model based on least square support vector machine optimized by leave-one-out cross-validation
Li, Feng
Tang, Bao-Ping
Zhang, Guo-Wen
Zhendong yu Chongji/Journal of Vibration and Shock, 2010, 29 (09): : 170 - 174

← 1 2 3 4 5 →