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NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques

arXiv 2401.17200 ↗First posted 30 Jan 2024cs.LG cs.AI cs.CVcited by 0

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Abstract (arXiv)

This paper presents a comprehensive comparative analysis of explainable artificial intelligence (XAI) ensembling methods. Our research brings three significant contributions. Firstly, we introduce a novel ensembling method, NormEnsembleXAI, that leverages minimum, maximum, and average functions in conjunction with normalization techniques to enhance interpretability. Secondly, we offer insights into the strengths and weaknesses of XAI ensemble methods. Lastly, we provide a library, facilitating the practical implementation of XAI ensembling, thus promoting the adoption of transparent and interpretable deep learning models.

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References · 36

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24 more
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