A novel feature engineered-CatBoost-based supervised machine learning framework for electricity theft detection

A novel feature engineered-CatBoost-based supervised machine learning framework for electricity theft detection

This paper presents a novel supervised machine learning-based electric theft detection approach using the feature engineered-CatBoost algorithm in conjunction with the SMOTETomek algorithm. Contrary to the previous literature, where the missing observations in data are either ignored or imputed with...

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Bibliographic Details
Main Authors: Saddam Hussain, Mohd. Wazir Mustafa, Touqeer A. Jumani, Shadi Khan Baloch, Hammad Alotaibi, Ilyas Khan, Afrasyab Khan
Format: Article
Language:English
Published: Elsevier 2021-11-01
Series:Energy Reports
Subjects:
CatBoost algorithm
NTL detection
Smart meters
Feature engineering
Machine learning model interpretation
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484721004716

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http://www.sciencedirect.com/science/article/pii/S2352484721004716

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