A Comparative Study on the Influence of Undersampling and Oversampling Techniques for the Classification of Physical Activities Using an Imbalanced Accelerometer Dataset.

Jeong, Dong-Hwa; Kim, Se-Eun; Choi, Woo-Hyeok; Ahn, Seong-Ho

Jeong, Dong-Hwa; Kim, Se-Eun; Choi, Woo-Hyeok; Ahn, Seong-Ho.

Afiliación

Jeong DH; Department of Artificial Intelligence, The Catholic University of Korea, Bucheon 14662, Korea.
Kim SE; School of Computer Science and Information Engineering, The Catholic University of Korea, Bucheon 14662, Korea.
Choi WH; School of Computer Science and Information Engineering, The Catholic University of Korea, Bucheon 14662, Korea.
Ahn SH; Department of Artificial Intelligence, The Catholic University of Korea, Bucheon 14662, Korea.

Healthcare (Basel) ; 10(7)2022 Jul 05.

Article en En | MEDLINE | ID: mdl-35885782

Palabras clave

accelerometer; adaptive boosting; bootstrap aggregating (bagging); ensemble method; oversampling; physical activity; random forest; undersampling

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Healthcare (Basel) Año: 2022 Tipo del documento: Article

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