Decoding the synergy: unveiling gradient boosting regression model for multivariate quantitation of pioglitazone, alogliptin and glimepiride in pure and tablet dosage forms

Decoding the synergy: unveiling gradient boosting regression model for multivariate quantitation of pioglitazone, alogliptin and glimepiride in pure and tablet dosage forms

Abstract This study represents a comparison among the performances of four multivariate procedures: partial least square (PLS) and artificial neural networks (ANN) in addition to support vector regression (SVR) and extreme gradient boosting (XG Boost) algorithm for the determination of the anti-diab...

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Bibliographic Details
Main Authors: Mahmoud M. Elkhoudary, Aya A. Marie, Sherin F. Hammad, Mohamed M. Salim, Amira H. Kamal
Format: Article
Language:English
Published: BMC 2024-11-01
Series:BMC Chemistry
Subjects:
Partial least squares
UV/Vis spectroscopy
Artificial neural networks
Extreme gradient boosting algorithm
Support vector regression
Online Access:https://doi.org/10.1186/s13065-024-01351-8

Internet

https://doi.org/10.1186/s13065-024-01351-8

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