The regularization paths for the ROC-optimizing support vector machines
- Authors
- Kim, Dohyun; Shin, Seung Jun
- Issue Date
- 3월-2020
- Publisher
- SPRINGER HEIDELBERG
- Keywords
- Support vector machine; Piecewise linearity; Unbalanced classification; Receiver operating characteristic curve
- Citation
- JOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.49, no.1, pp.264 - 275
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- JOURNAL OF THE KOREAN STATISTICAL SOCIETY
- Volume
- 49
- Number
- 1
- Start Page
- 264
- End Page
- 275
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/57469
- DOI
- 10.1007/s42952-019-00017-9
- ISSN
- 1226-3192
- Abstract
- Rakotomamonjy (RO-CAI, pp 71-80, 2009) proposed an ROC-SVM that optimizes the receiver operating characteristic curve (ROC) particularly useful for unbalanced classification. In this article, we establish the piecewise linearity of the ROC-SVM solutions as a function of regularization parameter, and develop an efficient algorithm for computing the entire regularization paths of the ROC-SVM. Finally we develop an R package, rocsvm.path, now available in CRAN.
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Collections - College of Political Science & Economics > Department of Statistics > 1. Journal Articles
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