Mobile Money Fraud Prediction - A Cross-Case Analysis on the Efficiency of Support Vector Machines, Gradient Boosted Decision Trees, and Naïve Bayes Algorithms

Francis Effirim Botchey, Zhen Qin, Kwesi Hughes-Lartey. Mobile Money Fraud Prediction - A Cross-Case Analysis on the Efficiency of Support Vector Machines, Gradient Boosted Decision Trees, and Naïve Bayes Algorithms. Information, 11(8):383, 2020. [doi]

@article{BotcheyQH20,
  title = {Mobile Money Fraud Prediction - A Cross-Case Analysis on the Efficiency of Support Vector Machines, Gradient Boosted Decision Trees, and Naïve Bayes Algorithms},
  author = {Francis Effirim Botchey and Zhen Qin and Kwesi Hughes-Lartey},
  year = {2020},
  doi = {10.3390/info11080383},
  url = {https://doi.org/10.3390/info11080383},
  researchr = {https://researchr.org/publication/BotcheyQH20},
  cites = {0},
  citedby = {0},
  journal = {Information},
  volume = {11},
  number = {8},
  pages = {383},
}