Enhancing predictive modeling across industries with automated machine learning: applications in insurance and agriculture

Enhancing predictive modeling across industries with automated machine learning: applications in insurance and agriculture

Abstract This study explores the efficacy of Automated Machine Learning (AutoML) tools in enhancing linear regression models across industries, focusing on insurance and agriculture. We assessed six widely used AutoML libraries—AutoKeras, AutoGluon, Hyperopt, MLJAR, LightAutoML, and H2O—on a Kaggle-...

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Bibliographic Details
Main Authors: K. P. Swain, S. K. Mohapatra, Santosh Kumar Sahoo
Format: Article
Language:English
Published: Springer 2025-03-01
Series:Discover Sustainability
Subjects:
Automated machine learning
Predictive analytics
Insurance analytics
Agricultural optimization
Sustainable development goals (SDGs)
Machine learning pipelines
Online Access:https://doi.org/10.1007/s43621-025-00965-9
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https://doi.org/10.1007/s43621-025-00965-9

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