Recycled Car Price Extrapolation by LASSO and Linear Regression

Given the fluidity of the used automobile market, appraising the value of a recycled car may be difficult and entail a number of variables. Predicting the price of recycled car by using machine learning can have positive effects on the economy, the environment, and society. It can also increase market transparency and open up new business options. The used car market in India is a booming industry, it was valued at $32.14 billion, and it is expected to reach $74.70 billion in the coming years. Though COVID-19 has affected a number of industries, the used car market has been minimally impacted by it. A huge amount of people wanting a personal vehicle of their own and the increase in car prices leads more people to buy used cars. As a result, the market for old cars will expand. We have attempted to forecast used car prices with this statistical model by utilizing machine learning techniques such as LASSO (least absolute shrinkage and selection operator) regression and linear regression. This model is based on information gathered from past customers and a variety of automotive attributes. We attempted to determine a certain percentage of the anticipated price’s accuracy with the aid of this model.