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About this paper
Sara Gjorgjieva, Ilinka Ivanoska, Marjan Gusev
The authors compare four automated hyperparameter optimization methods across six models for atrial fibrillation detection from ECG data, using F1 to score configurations. Hyperband-tuned XGBoost reaches an F1 of 96.95% in E22, with LTAFDB used for both training and testing in an 80/20 intra-patient split. This result does not establish cross-dataset generalization.
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