Modelling the Common Agricultural Policy Impact over the EU Agricultural and Rural Environment through a Machine Learning Predictive Framework

This research provides an analytical and predictive framework, based on state-of-the-art machine-learning (ML) algorithms (random forest (RF) and generalized additive models (GAM)), that can be used to assess and improve the Common Agricultural Policy (CAP) impact/performance over the agricultural a...

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Autores principales:	Dragos Sebastian Cristea, Sarina Rosenberg, Adriana Pustianu Mocanu, Ira Adeline Simionov, Alina Antache Mogodan, Stefan Mihai Petrea, Liliana Mihaela Moga
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	common agricultural policy random forest machine learning generalized additive model agriculture rural development Agriculture S
Acceso en línea:	https://doaj.org/article/561dd661057d446eb59b651eeda44522
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Modelling the Common Agricultural Policy Impact over the EU Agricultural and Rural Environment through a Machine Learning Predictive Framework

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