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The regularization paths for the ROC-optimizing support vector machines

Authors
Kim, DohyunShin, 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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