ANTICIPATION OF USED CAR PRICE PREDICTION

Computer Engineering

In this fast-moving generation, the present study proposes the newer concept of predicting the prices of certain items. With an idea and motivation to help everyone we came up with a solution to get an appropriate estimate of one’s car using Machine Learning Techniques which will save a lot of time and money. A car price prediction has been a high interest research area, as it requires noticeable effort and knowledge of the field expert. Considerable number of distinct attributes is examined for the reliable and accurate prediction. The production of cars has been steadily increasing in the past decade, with over 70 million passenger cars being produced in the year 2016. This has given rise to the used car market, which on its own has become a booming industry. The recent advent of online portals has facilitated the need for both the customer and the seller to be better informed about the trends and patterns that determine the value of a used car in the market. To build a model for predicting the price of used cars in, we applied one of the machine learning techniques i.e., Linear Regression. Using linear regression, there are multiple independent variables, but one and only one dependent variable whose actual and predicted values are compared to find precision of results. Our pro proposes a system where price is dependent variable which is predicted, and this price is derived from factors like kilometers driven.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.