Heuristic XAI: AIME and HMM Integration Improved-Feature-Importance Assessment Through Heuristics

Heuristic XAI: AIME and HMM Integration Improved-Feature-Importance Assessment Through Heuristics

The explainability of AI and machine learning models has become crucial, drawing significant attention to explainable AI (XAI) technologies. Global feature importance extraction is key to understanding the behavior of these models. However, existing XAI techniques often overlook the effects of multi...

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Bibliographic Details
Main Authors: Takafumi Nakanishi, Ponlawat Chophuk, Krisana Chinnasarn
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Approximate inverse model explanations (AIME)
explainable artificial intelligence (XAI)
feature selection
global feature importance
heuristics
Online Access:https://ieeexplore.ieee.org/document/10945308/
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