Proposal of self and semi-supervised learning for imbalanced classification of coronary heart disease tabular data
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. Medical tabular datasets are known to present challenges as...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Instituto Tecnológico de Costa Rica
2024-09-01
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| Series: | Tecnología en Marcha |
| Subjects: | |
| Online Access: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7295 |
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