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A comparison of learning methods over raw data: forecasting cab services market share in New York City

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Abstract

The cab services, present in most of the cities, are one of the most used offerings for passenger transportation. Nowadays their business model is being threatened by the meddling of emerging third parties powered by modern technologies. Based on the New York cab data, we will make a comparison of several machine learning techniques (linear regression, support vector machines and random forest) for forecasting the amount of dollars spent in the cab service. The comparison of those methods will focus on the accuracy of their forecasts under several circumstances: real data applied to all features, some noisy data (real data with some uniform distributed noise added) applied to several key features and some estimated data (obtained from other statistical estimators) applied to the key features. The main goal of this comparison is to provide some data regarding the performance of those methods when they are used in conjunction with other estimators

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Acknowledgements

This research work was supported by Sungshin Women’s University. In addition, L.J.G.V. and A.L.S.O thanks the European Commission Horizon 2020 5G-PPP Programme (Grant Agreement number H2020-ICT-2014-2/671672-SELFNET - Framework for Self-Organized Network Management in Virtualized and Software-Defined Networks).

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Authors and Affiliations

  1. Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Information Technology and Computer Science, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040, Madrid, Spain

    Fernando Turrado García, Luis Javier García Villalba & Ana Lucila Sandoval Orozco

  2. Department of Convergence Security, Sungshin Women’s University, 249-1 Dongseon-Dong 3-ga, Seoul, 136-742, Korea

    Tai-Hoon Kim

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  1. Fernando Turrado García
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  2. Luis Javier García Villalba
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  3. Ana Lucila Sandoval Orozco
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  4. Tai-Hoon Kim
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Correspondence to Luis Javier García Villalba.

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Turrado García, F., García Villalba, L.J., Sandoval Orozco, A.L. et al. A comparison of learning methods over raw data: forecasting cab services market share in New York City. Multimed Tools Appl 78, 29783–29804 (2019). https://doi.org/10.1007/s11042-018-6285-x

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  • DOI: https://doi.org/10.1007/s11042-018-6285-x

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