Credit Card Fraud Detection Using AdaBoost and Majority Voting
Credit card fraud is a serious problem in financial services. Billions of dollars are lost due to credit card fraud every year. There is a lack of research studies on analyzing real-world credit card data owing to confidentiality issues. In this paper, machine learning algorithms are used to detect...
Saved in:
Main Authors: | Randhawa, Kuldeep, Loo, Chu Kiong, Seera, Manjeevan, Lim, Chee Peng, Nandi, Asoke K. |
---|---|
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers
2018
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/20919/ https://doi.org/10.1109/ACCESS.2018.2806420 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Credit card fraud and identity theft: a case study in Malaysia
by: Ya'Acob, Suraya, et al.
Published: (2018) -
A Convolutional Neural Network model for Credit Card Fraud detection
by: Gambo, Muhammad Liman, et al.
Published: (2022) -
Solving two-class classification problem using AdaBoost
by: Chan, Lih Heng, et al.
Published: (2009) -
Human emotion recognition for computer games player using AdaBoost algorithm / Muhamad Nur Adhwa Muhamad Shukri
by: Muhamad Shukri, Muhamad Nur Adhwa
Published: (2017) -
Personality affected robotic emotional model with associative memory for human-robot interaction
by: Masuyama, Naoki, et al.
Published: (2018)