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Machine Learning Algorithms in Statistical Modelling Bridging Theory and Application.


Article Information

Title: Machine Learning Algorithms in Statistical Modelling Bridging Theory and Application.

Authors: A. Ganapathi Rao, Sathish Krishna Anumula, Aditya Kumar Singh, Renukhadevi M, Y. Jeevan Nagendra Kumar, Tammineni Rama Tulasi

Journal: Journal of Neonatal Surgery

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30

Publisher: EL-MED-Pub Publishers

Country: Pakistan

Year: 2025

Volume: 14

Issue: 21S

Language: en

Keywords: Machine learning

Categories

Abstract

It involves the completely novel ways of integrating ML algorithms with traditional statistical modelling that has changed the way we analyze data, do predictive analytics or make decisions in the fields of the data. In this paper, we study some ML and statistical model connections to understand ways in which some modern ML algorithms help 'enrich' conventional models; we demonstrate how new algorithms improve performance, scale, flexibility and robustness of the traditional models. It shows that the hybrid models are of great improvement in predictive accuracy, robustness, and interpretability


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