反事实转移图：评估跨类转移质量
Counterfactual Transition Graphs: Evaluating Cross-Class Transition Quality
- Otto-von-Guericke University Magdeburg（马格德堡奥托·冯·格里克大学）
- Jagiellonian University（雅盖隆大学）
- Halmstad University（哈尔姆斯塔德大学）
- Center for Applied Intelligence Systems Research（应用智能系统研究中心）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究提出反事实转移图（CGT）以评估时间序列分类器的跨类转移质量，发现反事实可达性与分类器准确率相悖，且可对比不同反事实解释器的性能。
AI中文摘要：
针对时间序列分类器的反事实（CF）解释通常以单个样本为单位进行评估：对单个窗口进行何种最小编辑可翻转其预测结果？我们认为，诊断可解释性更具信息量的问题是结构性的：分类器如何将自身的各类别相互关联？我们提出反事实转移图（CGT），其中每个节点代表一个类别，每条边的权重为在 proximity-aware 检索扫描下，从一个原型到另一个原型的反事实转移可靠性。在一个六类手部动作任务中，我们构建的 CGT 呈现出非平凡拓扑结构，这是二元混淆矩阵无法预测的：它显示反事实可达性与分类器准确率并不一致，甚至与之相悖（15 对的 Spearman ρ=-0.37），即分类器划分最自信的边界，恰恰是分布内编辑最难以跨越的边界。我们的框架与方法无关，即任何反事实解释器均可使用。目前，我们用它对比基于替换的反事实与基于梯度的反事实：基于梯度的方法通过脱离数据流形可到达几乎所有类别，而基于替换的方法则保持在数据流形上，且在刚性边界上失效。
英文摘要：
Counterfactual (CF) explanations for time-series classifiers are usually evaluated one example at a time: what minimal edit flips this single window's prediction? We argue that the more informative question for diagnostic interpretability is structural: how does the classifier connect its own classes to each other? We propose a counterfactual transition graph (CGT) in which each node is a class and each edge weight is the CF reliability of the transition from one prototype to another under a proximity aware retrieval sweep. On a six-class hand-movement task, we induce a CGT that reveals a non-trivial topology, which is not predicted by the binary confusion matrix: it shows that counterfactual reachability does not align with classifier accuracy and even runs counter to it (Spearman $ρ=-0.37$ over the 15 pairs), i.e. the boundaries the classifier separates most confidently are among those an in-distribution edit can least often cross. Our framework is method agnostic, i.e. any CF-explainers can be used. Presently, we use it to juxtapose replacement-based CFs with gradient-based CFs; gradient-based methods reach almost any class by stepping off the data manifold, while replacement-based methods stay on it and fail on precisely the rigid boundaries.
