Assefaw Gebremedhin

Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics

Evaluating machine learning models is crucial not only for determining their technical accuracy but also for assessing their potential societal implications. While the potential for low-sample-size bias in algorithms is well known, we demonstrate the significance of sample-size bias induced by combi…