文献
J-GLOBAL ID:201702291287915104
整理番号:17A0910228
ランプ損失Kサポートベクトル分類-回帰:侵入検出問題に対するロバストなとスパース多クラスアプローチ【Powered by NICT】
Ramp loss K-Support Vector Classification-Regression; a robust and sparse multi-class approach to the intrusion detection problem
著者 (9件):
Hosseini Bamakan Seyed Mojtaba
(Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)
,
Hosseini Bamakan Seyed Mojtaba
(Research center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China)
,
Hosseini Bamakan Seyed Mojtaba
(School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)
,
Wang Huadong
(Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)
,
Wang Huadong
(Research center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China)
,
Shi Yong
(Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China)
,
Shi Yong
(Research center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China)
,
Shi Yong
(School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)
,
Shi Yong
(College of Information Science and Technology, University of Nebraska at Omaha, 68182, NE, USA)
資料名:
Knowledge-Based Systems
(Knowledge-Based Systems)
巻:
126
ページ:
113-126
発行年:
2017年
JST資料番号:
T0426A
ISSN:
0950-7051
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)