Predicting Strength of High-Performance Concrete Using Gradient Boosting Machine Learning: A Comparative Analysis Between Manual and Grid Search Cross-Validation Hyperparameter Tuning

This study evaluates the effectiveness of a gradient boosting regression model in forecasting concrete strength by comparing three hyperparameter configurations: default settings, manual tuning, and automated Grid Search CV. A publicly available dataset of 1030 concrete mixes, featuring cement, slag...

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Bibliographic Details

Main Authors:	Ryan Tyler, Masengo Ilunga, Bolanle Ikotun, Omphemetse Zimbili
Format:	Artigo
Language:	Inglês
Published:	International Institute of Informatics and Cybernetics 2025-10-01
Series:	Journal of Systemics, Cybernetics and Informatics
Subjects:	high-performance concrete compressive strength gradient boosting hyperparameter tuning error evaluation
Online Access:	http://www.iiisci.org/Journal/PDV/sci/pdfs/DW614MN25.pdf
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