A-PETE: Adaptive Prototype Explanations of Tree Ensembles
<|reference_start|>A-PETE: Adaptive Prototype Explanations of Tree Ensembles: The need for interpreting machine learning models is addressed through prototype explanations within the context of tree ensembles. An algorithm named Adaptive Prototype Explanations of Tree Ensembles (A-PETE) is proposed to automatise the selection of prototypes for these classifiers. Its unique characteristics is using a specialised distance measure and a modified k-medoid approach. Experiments demonstrated its competitive predictive accuracy with respect to earlier explanation algorithms. It also provides a a sufficient number of prototypes for the purpose of interpreting the random forest classifier.<|reference_end|>
@article{karolczak2024a-pete:,
    title={A-PETE: Adaptive Prototype Explanations of Tree Ensembles},
    author={Jacek Karolczak, and Jerzy Stefanowski},
    journal={arXiv preprint arXiv:2405.21036},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.21036},
    primaryClass={cs.LG}
}