Creating adaptive farm typologies using Naive Bayesian classification

The applicability of statistical typologies that capture farming systems diversity in innovation and development projects would increase if their adaptability would be enhanced, so that newly encountered farms can be classified and used to update the typology. In this paper we propose Naïve Bayesian...

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Detalles Bibliográficos
Autores principales: Paas, W., Groot, Jeroen C.J.
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://hdl.handle.net/10568/87896
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author Paas, W.
Groot, Jeroen C.J.
author_browse Groot, Jeroen C.J.
Paas, W.
author_facet Paas, W.
Groot, Jeroen C.J.
author_sort Paas, W.
collection Repository of Agricultural Research Outputs (CGSpace)
description The applicability of statistical typologies that capture farming systems diversity in innovation and development projects would increase if their adaptability would be enhanced, so that newly encountered farms can be classified and used to update the typology. In this paper we propose Naïve Bayesian (NB) classification as a method to allocate farms to types by using only a few variables, thus allowing the addition of new entries to a typology. We show for two example datasets that the performance of NB classification is already acceptable when 50% of the original survey dataset to construct the typology is used for training the NB classifier. For our datasets, the performance of Naïve Bayesian classification was improved when probabilities for observations to belong to multiple types were used, requiring a sample size of 30% of the survey dataset. Based on the results in this paper, we argue that NB classification is a powerful and promising statistical approach to increase the adaptability and usability of farm typologies.
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spelling CGSpace878962023-12-08T19:36:04Z Creating adaptive farm typologies using Naive Bayesian classification Paas, W. Groot, Jeroen C.J. farming systems data intensification The applicability of statistical typologies that capture farming systems diversity in innovation and development projects would increase if their adaptability would be enhanced, so that newly encountered farms can be classified and used to update the typology. In this paper we propose Naïve Bayesian (NB) classification as a method to allocate farms to types by using only a few variables, thus allowing the addition of new entries to a typology. We show for two example datasets that the performance of NB classification is already acceptable when 50% of the original survey dataset to construct the typology is used for training the NB classifier. For our datasets, the performance of Naïve Bayesian classification was improved when probabilities for observations to belong to multiple types were used, requiring a sample size of 30% of the survey dataset. Based on the results in this paper, we argue that NB classification is a powerful and promising statistical approach to increase the adaptability and usability of farm typologies. 2017-09 2017-09-19T08:42:10Z 2017-09-19T08:42:10Z Journal Article https://hdl.handle.net/10568/87896 en Open Access Elsevier Paas, W. and Groot, J.C.J. 2017. Creating adaptive farm typologies using Naive Bayesian classification. Information Processing in Agriculture 4(3): 220-227.
spellingShingle farming systems
data
intensification
Paas, W.
Groot, Jeroen C.J.
Creating adaptive farm typologies using Naive Bayesian classification
title Creating adaptive farm typologies using Naive Bayesian classification
title_full Creating adaptive farm typologies using Naive Bayesian classification
title_fullStr Creating adaptive farm typologies using Naive Bayesian classification
title_full_unstemmed Creating adaptive farm typologies using Naive Bayesian classification
title_short Creating adaptive farm typologies using Naive Bayesian classification
title_sort creating adaptive farm typologies using naive bayesian classification
topic farming systems
data
intensification
url https://hdl.handle.net/10568/87896
work_keys_str_mv AT paasw creatingadaptivefarmtypologiesusingnaivebayesianclassification
AT grootjeroencj creatingadaptivefarmtypologiesusingnaivebayesianclassification