PREDICTION THE PRICE OF USED CAR USING MACHINE LEARNING

Abstract

Due to the obvious level of expertise and effort required, the prediction of automobile prices has been 
a popular topic of study. In order to make a solid and precise forecast, a large number of different 
characteristics are researched. In order to construct a model that can foretell the value of pre-owned 
automobiles. Machine learning techniques such as logistic regression, Random Forest, Support Vector 
Machine, and linear regression were used. But the aforementioned methods were used in conjunction 
with one another to do regressions and ensemble work. The information that went into making the 
forecast was gathered Then, in order to determine which method is most suited to the given data set, 
their respective results were compared. Predicting the optimal percentage and revealing the outcome 
with the appropriate algorithms are both tasks that need the use of algorithms.