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This Author published in this journals
All Journal Formosa Journal of Science and Technology (FJST)
O.O Owolabi
Adeleke University
Humanities Computer Science & IT Education Industrial & Manufacturing Engineering Social Sciences

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An Inquiry into Factors Responsible for Demand of Automobiles Using a Supervised Machine Learning Approach A.O Akinrotimi; J.O Atoyebi; O.O Owolabi; M.A Mabayoje
Formosa Journal of Science and Technology Vol. 4 No. 5 (2025): May 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v4i5.70

Abstract

This study investigates the primary drivers of automobile demand using a supervised machine learning approach. Feature selection was performed using the Minimum Redundancy Maximum Relevance (mRMR) algorithm to identify the most influential variables. The analysis reveals that sedans (46.83%) and hatchbacks (34.15%) are the most preferred body styles, with a strong inclination toward vehicles featuring four doors (56.10%) and front-wheel drive (58.54%). Front-engine layouts dominate (98.54%), likely due to cost-efficiency and mechanical simplicity. These findings provide valuable insights for data-driven inventory and sales management, enabling automotive retailers to better align their offerings with consumer preferences. The study highlights the potential of machine learning to enhance decision-making and operational efficiency in the automotive sector.
Co-Authors A.O Akinrotimi J.O Atoyebi M.A Mabayoje