Article

Predicting health effects of food compounds via ensemble machine learning

2023-06-05

Abstract excerpt

Identifying chemical compounds in foods and assaying their bioactivities significantly contribute to promoting human health. In this work, we propose a machine learning framework to predict 101 classes of health effects of food compounds at a large scale. To tackle skewedness of class distributions commonly encountered in chemobiological computing, we adopt random undersampling boosting (RUSBoost) as the base lear...

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Literature Corpus work: 47054d7b-f78d-5f03-a832-e08c7d91bfc8
DOI: 10.21203/rs.3.rs-2991763/v1

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