Article citationsMore>>

He, H., & Garcia, E. A. (2009). Learning from Imbalanced Data. IEEE Transactions on Knowledge and Data Engineering, 21, 1263-1284.
https://doi.org/10.1109/TKDE.2008.239

has been cited by the following article:

• TITLE: Adaptive Financial Fraud Detection in Imbalanced Data with Time-Varying Poisson Processes

  AUTHORS: Régis Houssou, Jérôme Bovay, Stephan Robert

  KEYWORDS: Homogeneous Poisson Process, Inhomogeneous Poisson Process, Intensity Model, Fraud Detection, Imbalanced Data

  JOURNAL NAME: Journal of Financial Risk Management, Vol.8 No.4, December 30, 2019

  ABSTRACT: This paper discusses financial fraud detection in imbalanced dataset using homogeneous and non-homogeneous Poisson processes. The probability of predicting fraud on the financial transaction is derived. Applying our methodology to financial datasets with different fraud profiles shows a better predicting power than a baseline approach, especially in the case of higher imbalanced data.