Application of the Representative Measure Approach to Assess the Reliability of Decision Trees in Dealing with Unseen Vehicle Collision Data
Published in Springer, 2024
In this paper, we provide a result guaranteeing that if two datasets are related by epsilon-representativeness, i.e., both of them have points closer than epsilon, then the predictions by the classic decision tree are similar. Experimentally, we have also tested that epsilon-representativeness presents a significant correlation with the ordering of the feature importance.
Recommended citation: Perera-Lago, J., Toscano-Duran, V., Paluzo-Hidalgo, E., Narteni, S., Rucco, M. (2024). Application of the Representative Measure Approach to Assess the Reliability of Decision Trees in Dealing with Unseen Vehicle Collision Data. In: Longo, L., Lapuschkin, S., Seifert, C. (eds) Explainable Artificial Intelligence. xAI 2024. Communications in Computer and Information Science, vol 2156. Springer, Cham. https://doi.org/10.1007/978-3-031-63803-9_21
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