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...
Guardado en:
Autores principales: | Dragos Sebastian Cristea, Sarina Rosenberg, Adriana Pustianu Mocanu, Ira Adeline Simionov, Alina Antache Mogodan, Stefan Mihai Petrea, Liliana Mihaela Moga |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/561dd661057d446eb59b651eeda44522 |
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