Retracted: An Automated Cost Prediction in Uber/Call Taxi Using Machine Learning Algorithm
Elizabeth Rani. G, M Sakthimohan, Revanth Raj. R, Sri Ganesh. M, Shyam Sunder. R, K. Karthigadevi
Abstract
Uber, Ola, Meru Cabs, and other cab businesses have sprung up in recent years. And these taxi firms serve tens of thousands of people every day. It is now critical for them to correctly manage their data in order to come up with fresh business ideas and get the greatest outcomes. As a result, it becomes critical to precisely predict the fares. The motive of this paper is to compare all the fare details of specified cabs and predict the lowest fare cab using linear regression method. In this paper we implemented prediction model for the three models like Uber Go, Go Sedan and Uber Auto. Here deviation of the cab fares also compared and using these data, build an application that can assist the users to select the cab with the determined benefits and lowest fare. In this model we use machine learning technique of linear Regression model, and it may contain labelled data. Here the methodology and outcomes of this work can contribute to a more real-world demand. This application can improve the transport accessibility, reduce waiting time and reduce the transportation fare etc.