mlsanityData to 14 Oct 2026

Machine Learning Algorithms in Statistical Modelling Bridging Theory and Application

arXiv 2511.04918 ↗First posted 7 Nov 2025cs.LGcited by 0

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Abstract (arXiv)

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

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 16 references that are in the map. First posted on arXiv 7 Nov 2025.

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References · 1

  1. 2021Bridging observation, theory and numerical simulation of the ocean using Machine Learningcited by 15

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