Open AccessPredicting True Value of Used Car using Multiple Linear Regression Model
Author(s) -
Laveena D'costa,
A. L. Wilson,
D. Souza,
M. Deepthi,
St Aloysius
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e1010.0285s20
Subject(s) - factory (object oriented programming) , linear regression , value (mathematics) , regression analysis , computer science , linear model , econometrics , regression , statistics , mathematics , machine learning , programming language
Predicting the true value of used cars requires lot of analysis. This prediction takes into account variables such as car model, fuel type, number of owner and so on. In this paper we are applying machine learning algorithms to determine the true value of cars when selling them to the dealers. We have used multiple linear regression model by dividing the data into training and test. Vehicle price forecast is both a critical and significant job, particularly when the car is used and does not come directly from the factory.