A Calibrated Ensemble Algorithm to Address Data Heterogeneity in Machine Learning: An Application to Identify Severe SLE Flares in Lupus Patients
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DOI: 10.1109/access.2022.3149477
Abstract: Motivated to address the inconsistency between the essential i.i.d. assumption in machine learning theory and the data heterogeneity in real-world applications, we propose a novel calibrated ensemble (CE) algorithm to facilitate learning with diverse data… read more here.
Keywords: calibrated ensemble; machine; data heterogeneity; machine learning ... See more keywords