Comparative evaluation of machine learning models for predicting Cimbex quadrimaculata population density across multiple problem formulations

Yunus Güral

doi:10.1371/journal.pone.0346494

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Open Access

Peer-reviewed

Research Article

Comparative evaluation of machine learning models for predicting Cimbex quadrimaculata population density across multiple problem formulations

Yunus Güral

Roles Conceptualization, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: ygural@firat.edu.tr

Affiliation Faculty of Science, Department of Statistics, Firat University, Elazığ, Türkiye

https://orcid.org/0000-0002-0572-453X

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Comparative evaluation of machine learning models for predicting Cimbex quadrimaculata population density across multiple problem formulations

Yunus Güral

Published: April 3, 2026
https://doi.org/10.1371/journal.pone.0346494

About the Authors

Yunus Güral

Roles Conceptualization, Formal analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: ygural@firat.edu.tr

Affiliation Faculty of Science, Department of Statistics, Firat University, Elazığ, Türkiye

https://orcid.org/0000-0002-0572-453X

Competing Interests

The authors have declared that no competing interests exist.

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Machine learning algorithms
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Trees
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Humidity
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Population density
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Decision tree learning
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