1. Used Cars Price Prediction using Machine Learning with Optimal Features
- Author
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Muhammad Jam e Kausar Ali Asghar, Samina Yasin, Zimal Mehboob Khan, and Khalid Mehmood
- Subjects
Computer science ,business.industry ,Purchasing power ,Machine learning ,computer.software_genre ,Purchasing ,Regression ,Ordinary least squares ,Value (economics) ,Linear regression ,Artificial intelligence ,Market value ,business ,computer ,Statistical hypothesis testing - Abstract
We all are needed the personal vehicle that could help us to travel from home to office and travel to vocations means we need the personal vehicle for traveling for this we purchase the new vehicle or used vehicle this is some time take so much to take decision for purchasing the new one and most difficult decision is to take how to sale the old one that is already we have keep using if we sale and what is best price we can get or gives us more benefits. More over the purchasing power of the customers is low due to the prices of the new cars. There are different methods to predict the price of the car according to market value. Our proposed method helps the both the purchase and seller for to purchase and sale their vehicle and they can predict the best for their vehicle and make their decision good for personal and business. Our proposed model performance shows that the proposed study is productive and efficient. In the proposed study the machine learning algorithm Regression helps in the outperform. Here we use the Statistical test to get the design value of P and get the optimal features and using the linear regression. First, we find the RFE and then apply the statistical test for VIF for the OLS Regression. Prediction results shows the study is efficient and effective.
- Published
- 2021
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