Machine-learning models for activity class prediction: A comparative study of feature selection and classification algorithms.
Purpose: Machine-learning (ML) approaches have been repeatedly coupled with raw accelerometry to classify physical activity classes, but the features required to optimize their predictive performance are still unknown. Our aim was to identify appropriate combination of feature subsets and prediction...
| Publicado en: | Gait & Posture Vol. 89; pp. 45 - 54 |
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| Autores principales: | , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Sep2021
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| Acceso en línea: | Ver este registro en EBSCOhost |