Fast Estimation Method for the Stability of Ensemble Feature Selectors

Autor: Onda, Rina, Gao, Zhengyan, Kotera, Masaaki, Oono, Kenta

It is preferred that feature selectors be \textit{stable} for better interpretabity and robust prediction. Ensembling is known to be effective for improving the stability of feature selectors. Since ensembling is time-consuming, it is desirable to re

Externí odkaz: http://arxiv.org/abs/2108.01485

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Assessment of Multidimensional Health Care Parameters Among Adults in Japan for Developing a Virtual Human Generative Model: Protocol for a Cross-sectional Study.

Autor: Hibi M; Biological Science Research, Kao Corporation, Tokyo, Japan., Katada S; Biological Science Research, Kao Corporation, Tokyo, Japan., Kawakami A; Digital Business Creation, Kao Corporation, Tokyo, Japan., Bito K; Digital Business Creation, Kao Corporation, Tokyo, Japan., Ohtsuka M; Biological Science Research, Kao Corporation, Tochigi, Japan., Sugitani K; Biological Science Research, Kao Corporation, Tokyo, Japan., Muliandi A; Biological Science Research, Kao Corporation, Tokyo, Japan., Yamanaka N; Biological Science Research, Kao Corporation, Tokyo, Japan., Hasumura T; Biological Science Research, Kao Corporation, Tokyo, Japan., Ando Y; Biological Science Research, Kao Corporation, Tokyo, Japan., Fushimi T; Biological Science Research, Kao Corporation, Tokyo, Japan., Fujimatsu T; Biological Science Research, Kao Corporation, Tochigi, Japan., Akatsu T; Biological Science Research, Kao Corporation, Tochigi, Japan., Kawano S; Biological Science Research, Kao Corporation, Tochigi, Japan., Kimura R; Analytical Science Research, Kao Corporation, Tochigi, Japan., Tsuchiya S; Analytical Science Research, Kao Corporation, Tochigi, Japan., Yamamoto Y; Analytical Science Research, Kao Corporation, Tochigi, Japan., Haneoka M; Analytical Science Research, Kao Corporation, Tochigi, Japan., Kushida K; Analytical Science Research, Kao Corporation, Tochigi, Japan., Hideshima T; Analytical Science Research, Kao Corporation, Tochigi, Japan., Shimizu E; Analytical Science Research, Kao Corporation, Tochigi, Japan., Suzuki J; Analytical Science Research, Kao Corporation, Tochigi, Japan., Kirino A; Analytical Science Research, Kao Corporation, Tochigi, Japan., Tsujimura H; Analytical Science Research, Kao Corporation, Tochigi, Japan., Nakamura S; Analytical Science Research, Kao Corporation, Tochigi, Japan., Sakamoto T; Sensory Science Research, Kao Corporation, Tokyo, Japan., Tazoe Y; Sensory Science Research, Kao Corporation, Tokyo, Japan., Yabuki M; Sensory Science Research, Kao Corporation, Tokyo, Japan., Nagase S; Hair Care Products Research, Kao Corporation, Tokyo, Japan., Hirano T; Hair Care Products Research, Kao Corporation, Tokyo, Japan., Fukuda R; Hair Care Products Research, Kao Corporation, Tokyo, Japan., Yamashiro Y; Personal Health Care Products Research, Kao Corporation, Tokyo, Japan., Nagashima Y; Personal Health Care Products Research, Kao Corporation, Tokyo, Japan., Ojima N; Personal Health Care Products Research, Kao Corporation, Tokyo, Japan., Sudo M; Personal Health Care Products Research, Kao Corporation, Tokyo, Japan., Oya N; Biological Science Research, Kao Corporation, Tokyo, Japan., Minegishi Y; Biological Science Research, Kao Corporation, Tochigi, Japan., Misawa K; Biological Science Research, Kao Corporation, Tokyo, Japan., Charoenphakdee N; Preferred Networks, Inc, Tokyo, Japan., Gao Z; Preferred Networks, Inc, Tokyo, Japan., Hayashi K; Preferred Networks, Inc, Tokyo, Japan., Oono K; Preferred Networks, Inc, Tokyo, Japan., Sugawara Y; Preferred Networks, Inc, Tokyo, Japan., Yamaguchi S; Preferred Networks, Inc, Tokyo, Japan., Ono T; Ueno-Asagao Clinic, Tokyo, Japan., Maruyama H; Preferred Networks, Inc, Tokyo, Japan.; Research into Artifacts, Center for Engineering, The University of Tokyo, Tokyo, Japan.; Kao Corporation, Tokyo, Japan.

Publikováno v: JMIR research protocols [JMIR Res Protoc] 2023 Jun 09; Vol. 12, pp. e47024. Date of Electronic Publication: 2023 Jun 09.