On the Complexity of Global Necessary Reasons to Explain Classification

Fuente: arXiv
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Main Authors: Calautti, Marco, Malizia, Enrico, Molinaro, Cristian
Format: Preprint
Published: 2025
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author Calautti, Marco
Malizia, Enrico
Molinaro, Cristian
author_facet Calautti, Marco
Malizia, Enrico
Molinaro, Cristian
contents Explainable AI has garnered considerable attention in recent years, as understanding the reasons behind decisions or predictions made by AI systems is crucial for their successful adoption. Explaining classifiers' behavior is one prominent problem. Work in this area has proposed notions of both local and global explanations, where the former are concerned with explaining a classifier's behavior for a specific instance, while the latter are concerned with explaining the overall classifier's behavior regardless of any specific instance. In this paper, we focus on global explanations, and explain classification in terms of ``minimal'' necessary conditions for the classifier to assign a specific class to a generic instance. We carry out a thorough complexity analysis of the problem for natural minimality criteria and important families of classifiers considered in the literature.
format Preprint
id arxiv_https___arxiv_org_abs_2501_06766
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the Complexity of Global Necessary Reasons to Explain Classification
Calautti, Marco
Malizia, Enrico
Molinaro, Cristian
Artificial Intelligence
Explainable AI has garnered considerable attention in recent years, as understanding the reasons behind decisions or predictions made by AI systems is crucial for their successful adoption. Explaining classifiers' behavior is one prominent problem. Work in this area has proposed notions of both local and global explanations, where the former are concerned with explaining a classifier's behavior for a specific instance, while the latter are concerned with explaining the overall classifier's behavior regardless of any specific instance. In this paper, we focus on global explanations, and explain classification in terms of ``minimal'' necessary conditions for the classifier to assign a specific class to a generic instance. We carry out a thorough complexity analysis of the problem for natural minimality criteria and important families of classifiers considered in the literature.
title On the Complexity of Global Necessary Reasons to Explain Classification
topic Artificial Intelligence
url https://arxiv.org/abs/2501.06766