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

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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Bibliographic Details
Main Authors: Saddam Hussain, Mohd Wazir Mustafa, Khalil Hamdi Ateyeh Al-Shqeerat, Faisal Saeed, Bander Ali Saleh Al-rimy
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Sensors
Subjects:
theft detection in power consumption data
NGBoost algorithm
majority weighted minority oversampling technique algorithm
whale optimization algorithm
tree SHAP algorithm
Online Access:https://www.mdpi.com/1424-8220/21/24/8423

Internet

https://www.mdpi.com/1424-8220/21/24/8423

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