Hyperparameter Optimization with Genetic Algorithms and XGBoost: A Step Forward in Smart Grid Fraud Detection

Hyperparameter Optimization with Genetic Algorithms and XGBoost: A Step Forward in Smart Grid Fraud Detection

This study provides a comprehensive analysis of the combination of Genetic Algorithms (GA) and XGBoost, a well-known machine-learning model. The primary emphasis lies in hyperparameter optimization for fraud detection in smart grid applications. The empirical findings demonstrate a noteworthy enhanc...

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Bibliographic Details
Main Authors: Adil Mehdary, Abdellah Chehri, Abdeslam Jakimi, Rachid Saadane
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Sensors
Subjects:
genetic algorithms
XGBoost
hyperparameter optimization
fraud detection
smart grids
SGCC dataset
Online Access:https://www.mdpi.com/1424-8220/24/4/1230

Internet

https://www.mdpi.com/1424-8220/24/4/1230

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