Decoding ’Eligibility Unknown’: transparent classification and feature-based reclassification in CAFV analysis

Decoding ’Eligibility Unknown’: transparent classification and feature-based reclassification in CAFV analysis

This study introduces an interpretable machine learning model—ExplainableClassifier—to automate the classification of Clean Alternative Fuel Vehicle (CAFV) eligibility into three categories: Eligible, Not eligible due to low battery range, and Eligibility unknown. The model is trained on a refined d...

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Bibliographic Details
Main Authors: Muhammad Amir Khan, Mona A. Alkhattabi, Sheikh Muhammad Saqib, Tehseen Mazhar, Tariq Shahzad, Asim Seedahmed Ali Osman, Abdul Khader Jilani Saudagar, Habib Hamam
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:International Journal of Electrical Power & Energy Systems
Subjects:
CAFV (Clean alternative fuel vehicle)
Machine Learning
Explainable AI (XAI)
SHAP
LIME
Online Access:http://www.sciencedirect.com/science/article/pii/S0142061525004429
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http://www.sciencedirect.com/science/article/pii/S0142061525004429

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