文献
J-GLOBAL ID:202002288217898923
整理番号:20A0190958
SGL-SVM 疎群Lassoを用いたサポートベクトルマシンによる腫瘍分類のための新しい方法【JST・京大機械翻訳】
SGL-SVM: A novel method for tumor classification via support vector machine with sparse group Lasso
著者 (11件):
Huo Yanhao
(College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Huo Yanhao
(Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Xin Lihui
(School of Science, Dalian University of Technology, Panjin 124221, China)
,
Kang Chuanze
(College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Kang Chuanze
(Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Wang Minghui
(College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Wang Minghui
(Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Ma Qin
(Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio 43210, USA)
,
Yu Bin
(College of Mathematics and Physics, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Yu Bin
(Artificial Intelligence and Biomedical Big Data Research Center, Qingdao University of Science and Technology, Qingdao 266061, China)
,
Yu Bin
(School of Life Sciences, University of Science and Technology of China, Hefei 230027, China)
資料名:
Journal of Theoretical Biology
(Journal of Theoretical Biology)
巻:
486
ページ:
Null
発行年:
2020年
JST資料番号:
A0288B
ISSN:
0022-5193
CODEN:
JTBIA
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)