Proposal of self and semi-supervised learning for imbalanced classification of coronary heart disease tabular data by Danny Xie-Li, Manfred González-Hernández

“…Triple Mixup is an augmentation policy in the hidden latent space we introduced in the Contrastive Mixup Self-Semi Supervised learning framework, to address the imbalanced data problem, for Cardiovascular Heart Diseases tabular dataset. …”
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