Predicting tax fraud using supervised machine learning approach-Reference-Cited by-同舟云学术

Predicting tax fraud using supervised machine learning approach

Published:2023-04-09 Issue:6 Volume:15 Page:731-742
ISSN:2042-1338
Container-title:African Journal of Science, Technology, Innovation and Development
language:en
Short-container-title:African Journal of Science, Technology, Innovation and Development

Author:

Murorunkwere Belle Fille¹^ORCID,Haughton Dominique²,Nzabanita Joseph³^ORCID,Kipkogei Francis⁴^ORCID,Kabano Ignace⁵

Affiliation:

1. African Centre of Excellence in Data Science, University of Rwanda, Rwanda Revenue Authority

2. Bentley University, Université Paris 1 (SAMM), Université Toulouse 1 (TSE-R)

3. School of Science, College of Science and Technology, University of Rwanda

4. Zalda, Stepwise Inc, Nairobi, Kenya

5. African Centre of Excellence in Data Science, College of Business and Economics/University of Rwanda

Publisher

Informa UK Limited

Subject

Computer Networks and Communications,Computer Science Applications,Development,Civil and Structural Engineering

Link

Reference34 articles.

1. Abraham, A. 2005. Artificial Neural Networks: Handbook of Measuring System Design. Chichester: John Wiley & Sons, Ltd.

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Application of Machine Learning in Taxation: A Systematic Literature Review;2024 International Seminar on Intelligent Technology and Its Applications (ISITIA);2024-07-10