A framework to select a classification algorithm in electricity fraud detection
In the electrical domain, a non-technical loss often refers to energy used but not paid for by a consumer. The identification and detection of this loss is important as the financial loss by the electricity supplier has a negative impact on revenue. Several statistical and machine learning classifi...
Main Authors: | Sisa Pazi, Chantelle M. Clohessy, Gary D. Sharp |
---|---|
Format: | Article |
Language: | English |
Published: |
Academy of Science of South Africa
2020-09-01
|
Series: | South African Journal of Science |
Subjects: | |
Online Access: | https://www.sajs.co.za/article/view/8189 |
Similar Items
-
An Experimental Study With Imbalanced Classification Approaches for Credit Card Fraud Detection
by: Sara Makki, et al.
Published: (2019-01-01) -
Taxonomy of Fraud Detection Metrics for Business Processes
by: Badr Omair, et al.
Published: (2020-01-01) -
Presenting a Model for Financial Reporting Fraud Detection using Genetic Algorithm
by: Mahmood Mohammadi, et al.
Published: (2021-04-01) -
E-fraud E-fraud, state of the art and counter measures
by: Bergman, Bengt
Published: (2005) -
Ensemble Classification and Extended Feature Selection for Credit Card Fraud Detection
by: F. Fadaei Noghani, et al.
Published: (2017-07-01)