Classification of Max Rider’s Earning using Machine Learning

Authors : O.J. Timilehin; O.A. Balogun; M.A. Dosunmu

Volume/Issue : Volume 7 - 2022, Issue 1 - January

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This work looked into the ban of bike hailing activities which came into effect in the year 2020 by the Lagos state government. The work looked into the various angles that may have influenced this decision and what factors influenced the earning potential of bike riders. We made use of very limited data due to the reluctance of bike hailing companies to release more and initial analysis showed that there were a lot of discrepancies embedded in it. Using data pre-processing techniques, we were able to get more insight and carried out machine leaning classification operations consisting of Linear Regression, K-Nearest Neighbor, and Support Vector Classifiers to determine the most influencing earning factors. Results showed that all three methods performed averagely and it was recommended that more accurate and voluminous data will be required to predict better results.

Keywords : Transportation, Machine Learning, Information technology, Hailing services, Ban


Paper Submission Last Date
30 - June - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

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