Counterfactual explanation methods provide information on how feature values of individual observations must be changed to obtain a desired prediction. Despite the increasing amount of proposed methods in research, only a few implementations exist whose interfaces and requirements vary widely. In this work, we introduce the counterfactuals R package, which provides a modular and unified R6-based interface for counterfactual explanation methods. We implemented three existing counterfactual explanation methods and propose some optional methodological extensions to generalize these methods to different scenarios and to make them more comparable. We explain the structure and workflow of the package using real use cases and show how to integrate additional counterfactual explanation methods into the package. In addition, we compared the implemented methods for a variety of models and datasets with regard to the quality of their counterfactual explanations and their runtime behavior.

介绍了一个名为Counterfactuals的R包，提供模块化和统一的R6接口来解释Counterfactual explanation methods，并提出了一些可选的方法学扩展，以将这些方法推广到不同的情境中并使它们更可比。同时，将其应用于不同模型和数据集，对实现的方法进行了比较，评估其解释质量和运行效率。

反事实：一款用于反事实解释方法的 R 包