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

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Title: A Novel Feature-Engineered-NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data.
Authors: Hussain S; School of Electrical Engineering, University Technology Malaysia, Johor Bahru 81310, Malaysia., Mustafa MW; School of Electrical Engineering, University Technology Malaysia, Johor Bahru 81310, Malaysia., Al-Shqeerat KHA; Department of Computer Science, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia., Saeed F; School of Computing and Digital Technology, Birmingham City University, Birmingham B4 7XG, UK., Al-Rimy BAS; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia.
Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2021 Dec 17; Vol. 21 (24). Date of Electronic Publication: 2021 Dec 17.
Publication Type: Journal Article
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: A Novel Feature-Engineered-NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data.
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  Data: <searchLink fieldCode="AU" term="%22Hussain+S%22">Hussain S</searchLink>; School of Electrical Engineering, University Technology Malaysia, Johor Bahru 81310, Malaysia.<br /><searchLink fieldCode="AU" term="%22Mustafa+MW%22">Mustafa MW</searchLink>; School of Electrical Engineering, University Technology Malaysia, Johor Bahru 81310, Malaysia.<br /><searchLink fieldCode="AU" term="%22Al-Shqeerat+KHA%22">Al-Shqeerat KHA</searchLink>; Department of Computer Science, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia.<br /><searchLink fieldCode="AU" term="%22Saeed+F%22">Saeed F</searchLink>; School of Computing and Digital Technology, Birmingham City University, Birmingham B4 7XG, UK.<br /><searchLink fieldCode="AU" term="%22Al-Rimy+BAS%22">Al-Rimy BAS</searchLink>; School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia.
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  Data: <searchLink fieldCode="JN" term="%22101204366%22">Sensors (Basel, Switzerland)</searchLink> [Sensors (Basel)] 2021 Dec 17; Vol. 21 (24). <i>Date of Electronic Publication: </i>2021 Dec 17.
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        Value: 10.3390/s21248423
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        Text: English
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      – TitleFull: A Novel Feature-Engineered-NGBoost Machine-Learning Framework for Fraud Detection in Electric Power Consumption Data.
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              Text: 2021 Dec 17
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