Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior of ML models. XAI utilizes counterfactual explanations that...

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Bibliographic Details
Main Authors: Ebtisam AlJalaud, Manar Hosny
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Mathematics
Subjects:
explainable artificial intelligence
counterfactual explanation
genetic algorithm
machine learning
feature importance
Pearson correlation
Online Access:https://www.mdpi.com/2227-7390/12/23/3727
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