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11 September 2023 Machine learning modeling for reconditioned car selling price prediction
Fatema Abdullah, Md. Ataur Rahman, Mohammad Shidujaman, Mahady Hasan, Md. Tarek Habib
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Proceedings Volume 12779, Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023); 1277925 (2023) https://doi.org/10.1117/12.2689745
Event: Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023), 2023, Kunming, China
Abstract
Almost 80% of the vehicles required for Bangladesh's road transportation industry are supplied by reconditioned cars. Using Machine Learning (ML) to predict car prices refers to using ML algorithms and techniques to make assumption about future car prices. This can be useful for a variety of purposes, such as helping car buyers and sellers make informed decisions, assisting car dealerships with inventory management, or providing insights for car manufacturers and other industry stakeholders. To predict car prices using ML, data is collected on a variety of factors that can affect the ongoing cost of a car, such as its make and model, age, mileage, condition, and location. This data is then fed into the Random Forest ML model, which uses statistical techniques to analyze the data and identify patterns and trends. The model performs 99.59% accurately in the tested portion of the data set and ensures that the model can then be used to make predictions on the future cost of an automobile based on these patterns and trends.
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Fatema Abdullah, Md. Ataur Rahman, Mohammad Shidujaman, Mahady Hasan, and Md. Tarek Habib "Machine learning modeling for reconditioned car selling price prediction", Proc. SPIE 12779, Seventh International Conference on Mechatronics and Intelligent Robotics (ICMIR 2023), 1277925 (11 September 2023); https://doi.org/10.1117/12.2689745
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KEYWORDS
Data modeling
Machine learning
Performance modeling
Decision trees
Industry
Lawrencium
Linear regression
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