A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations
Abstract
Counterfactual explanations constitute among the most popular methods for analyzing black-box systems since they can recommend cost-efficient and actionable changes to the input of a system to obtain the desired system output. While most of the existing counterfactual methods explain a single instance, several real-world problems, such as customer satisfaction, require the identification of a single counterfactual that can satisfy multiple instances (e.g. customers) simultaneously. To address this limitation, in this work, we propose a flexible two-stage algorithm for finding groups of instances and computing cost-efficient multi-instance counterfactual explanations. The paper presents the algorithm and its performance against popular alternatives through a comparative evaluation.
Cite
@article{arxiv.2403.01221,
title = {A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations},
author = {André Artelt and Andreas Gregoriades},
journal= {arXiv preprint arXiv:2403.01221},
year = {2024}
}
Comments
Accepted in the Late-breaking works track @ 2nd World Conference on eXplainable Artificial Intelligence (2024)