A machine learning approach using conditional normalizing flow to address extreme class imbalance problems in personal health records
Yeongmin Kim,
Wongyung Choi,
Woojeong Choi
et al.
Abstract:Background
Supervised machine learning models have been widely used to predict and get insight into diseases by classifying patients based on personal health records. However, a class imbalance is an obstacle that disrupts the training of the models. In this study, we aimed to address class imbalance with a conditional normalizing flow model, one of the deep-learning-based semi-supervised models for anomaly detection. It is the first introduction of the normalizing flow algorithm for tabular bi… Show more
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