Eliza Ayo

How Classification Models Degrade as Data Diminish: A Multi-Criteria Analysis of Tabular Classifiers Under Controlled Data Scarcity

Tree-based models exhibited the largest reductions in accuracy and the steepest increases in calibration error under scarcity, whereas logistic regression preserved threshold balance and probability calibration at negligible computational cost.