Standard
Multi-objective model selection for support vector machines. / Igel, Christian.
Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings. ed. / Carlos A. Coello Coello; Arturo Hernándex Aguirre; Eckart Zitzler. Springer, 2005. p. 534-546 (Lecture notes in computer science, Vol. 3410).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Igel, C 2005,
Multi-objective model selection for support vector machines. in CAC Coello, AH Aguirre & E Zitzler (eds),
Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings. Springer, Lecture notes in computer science, vol. 3410, pp. 534-546, 3rd International Conference on Evolutionary Multi-Criterion Optimization, Guanajuato, Mexico,
09/03/2005.
https://doi.org/10.1007/978-3-540-31880-4_37
APA
Igel, C. (2005).
Multi-objective model selection for support vector machines. In C. A. C. Coello, A. H. Aguirre, & E. Zitzler (Eds.),
Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings (pp. 534-546). Springer. Lecture notes in computer science Vol. 3410
https://doi.org/10.1007/978-3-540-31880-4_37
Vancouver
Igel C.
Multi-objective model selection for support vector machines. In Coello CAC, Aguirre AH, Zitzler E, editors, Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings. Springer. 2005. p. 534-546. (Lecture notes in computer science, Vol. 3410).
https://doi.org/10.1007/978-3-540-31880-4_37
Author
Igel, Christian. / Multi-objective model selection for support vector machines. Evolutionary Multi-Criterion Optimization: Third International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005. Proceedings. editor / Carlos A. Coello Coello ; Arturo Hernándex Aguirre ; Eckart Zitzler. Springer, 2005. pp. 534-546 (Lecture notes in computer science, Vol. 3410).
Bibtex
@inproceedings{003ec3915b8145649e4c1cb67f48b181,
title = "Multi-objective model selection for support vector machines",
abstract = "In this article, model selection for support vector machines is viewed as a multi-objective optimization problem, where model complexity and training accuracy define two conflicting objectives. Different optimization criteria are evaluated: Split modified radius margin bounds, which allow for comparing existing model selection criteria, and the training error in conjunction with the number of support vectors for designing sparse solutions.",
author = "Christian Igel",
year = "2005",
doi = "10.1007/978-3-540-31880-4_37",
language = "English",
isbn = "978-3-540-24983-2",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "534--546",
editor = "Coello, {Carlos A. Coello} and Aguirre, {Arturo Hern{\'a}ndex} and Eckart Zitzler",
booktitle = "Evolutionary Multi-Criterion Optimization",
address = "Switzerland",
note = "null ; Conference date: 09-03-2005 Through 11-03-2005",
}
RIS
TY - GEN
T1 - Multi-objective model selection for support vector machines
AU - Igel, Christian
N1 - Conference code: 3
PY - 2005
Y1 - 2005
N2 - In this article, model selection for support vector machines is viewed as a multi-objective optimization problem, where model complexity and training accuracy define two conflicting objectives. Different optimization criteria are evaluated: Split modified radius margin bounds, which allow for comparing existing model selection criteria, and the training error in conjunction with the number of support vectors for designing sparse solutions.
AB - In this article, model selection for support vector machines is viewed as a multi-objective optimization problem, where model complexity and training accuracy define two conflicting objectives. Different optimization criteria are evaluated: Split modified radius margin bounds, which allow for comparing existing model selection criteria, and the training error in conjunction with the number of support vectors for designing sparse solutions.
U2 - 10.1007/978-3-540-31880-4_37
DO - 10.1007/978-3-540-31880-4_37
M3 - Article in proceedings
AN - SCOPUS:24344435631
SN - 978-3-540-24983-2
T3 - Lecture notes in computer science
SP - 534
EP - 546
BT - Evolutionary Multi-Criterion Optimization
A2 - Coello, Carlos A. Coello
A2 - Aguirre, Arturo Hernándex
A2 - Zitzler, Eckart
PB - Springer
Y2 - 9 March 2005 through 11 March 2005
ER -