文献
J-GLOBAL ID:201902269634796419
整理番号:19A2210557
社会経済的地位からの女性の身長の予測:機械学習アプローチ【JST・京大機械翻訳】
Predicting women’s height from their socioeconomic status: A machine learning approach
著者 (4件):
Daoud Adel
(Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Harvard University, United States)
,
Kim Rockli
(Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Harvard University, United States)
,
Subramanian S.V.
(Center for Population and Development Studies, Harvard T.H. Chan School of Public Health, Harvard University, United States)
,
Subramanian S.V.
(Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, United States)
資料名:
Social Science & Medicine
(Social Science & Medicine)
巻:
238
ページ:
Null
発行年:
2019年
JST資料番号:
A1143A
ISSN:
0277-9536
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)