Supplementary Materials Rashomon Capacity: A Metric for Predictive Multiplicity in Classification

(since we pick the log base to be 2). We now prove the converse statements. Individual fairness aims to ensure that "similar individuals are treated similarly." Predictive multiplicity allows different predictions from competing classifiers for the samples. Notably, neural networks with very narrows or wide layers have better reproducibility in their decision regions. The fact that multiple classifiers may yield distinct predictions to a target a sample while having statistically identical average loss performance can also cause security issues in machine learning.