ICSE 2023 (series) / Artifact Evaluation /
Artifact for the ICSE 2023 Paper Entitled "Towards Understanding Fairness and its Composition in Ensemble Machine Learning"
The artifact  contains code, data, and additional information for the ICSE 2023 paper entitled “Towards Understanding Fairness and its Composition in Ensemble Machine Learning" [2 ]. The study contributes ensemble datasets: a collection of 168 ensemble models from Kaggle on four popular fairness datasets to understand the composition of fairness in ensemble models. We look at homogeneous and heterogeneous ensembles across different ensemble types and categories (Refer to Table 1 in [ 2]). The usage instructions and further details can be found in our GitHub repository: https://github.com/UsmanGohar/FairEnsemble