Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study
Abstract We present a simple and efficient hypothesis-free machine learning pipeline for risk factor discovery that accounts for non-linearity and interaction in large biomedical databases with minimal variable pre-processing. In this study, mortality models were built using gradient boosting decisi...
Enregistré dans:
| Auteurs principaux: | , , , |
|---|---|
| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
|
| Sujets: | |
| Accès en ligne: | https://doaj.org/article/8d07dd6dd43b4072bad55c2c9fa43b2b |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Soyez le premier à ajouter un commentaire!