A Novel Feature-Engineered–NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data

This study presents a novel feature-engineered–natural gradient descent ensemble-boosting (NGBoost) machine-learning framework for detecting fraud in power consumption data. The proposed framework was sequentially executed in three stages: data pre-processing, feature engineering, and model evaluati...

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Detalles Bibliográficos
Autores principales: Hussain, Saddam, Mustafa, Mohd Wazir, Al-Shqeerat, Khalil Hamdi Ateyeh, Saeed, Faisal, Al-rimy, Bander Ali Saleh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8704372/
https://www.ncbi.nlm.nih.gov/pubmed/34960516
http://dx.doi.org/10.3390/s21248423

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8704372/
https://www.ncbi.nlm.nih.gov/pubmed/34960516
http://dx.doi.org/10.3390/s21248423

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