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Research Article | Open Access |

Using Decision Tree Classification Model to Predict Payment Type in NYC Yellow Taxi

Author 1: Hadeer Ismaeil Author 2: Sherif Kholeif Author 3: Manal A. Abdel-Fattah
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 13, No. 3 · Published 2022

DOI: https://doi.org/10.14569/IJACSA.2022.0130330

Abstract

The taxi services are growing rapidly as reliable services. The demand and competition between service providers is so high. A billion trip records need to be analyzed to raise the spirit of competition, understand the service users, and improve the business. Although decision tree classification is a common algorithm which generates rules that are easy to understand, there is no implementation for classification on taxi dataset. This research applies the decision tree classification model on taxi dataset to classify instances correctly, build a decision tree, and calculate accuracy. This experiment collected decision tree algorithm with Spark framework to present the good performance and high accuracy when predicting payment type. Applied decision tree algorithm with different aspects on NYC taxi dataset results in high accuracy.

Keywords

How to Cite this Article

Ismaeil, H., Kholeif, S., & Abdel-Fattah, M. A. (2022). Using Decision Tree Classification Model to Predict Payment Type in NYC Yellow Taxi. International Journal of Advanced Computer Science and Applications, 13(3). https://doi.org/10.14569/IJACSA.2022.0130330

Ismaeil, Hadeer, et al.. "Using Decision Tree Classification Model to Predict Payment Type in NYC Yellow Taxi." International Journal of Advanced Computer Science and Applications, vol. 13, no. 3, 2022, https://doi.org/10.14569/IJACSA.2022.0130330.

@article{Ismaeil2022,
  title     = {Using Decision Tree Classification Model to Predict Payment Type in NYC Yellow Taxi},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {3},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Hadeer Ismaeil and Sherif Kholeif and Manal A. Abdel-Fattah},
  doi       = {10.14569/IJACSA.2022.0130330},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130330}
}

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