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Application of support vector machines to melissopalynological data for honey classifcation

Articolo
Data di Pubblicazione:
2010
Abstract:
In this paper, the authors address the problem of the discrimination of geographical origin and the selection of marker species of honeys using Support Vector Machines and z-scores. The methodology is based on the elaboration of palynological data with statistical learning methodologies. This innovative solution provides a simple yet powerful tool to detect the origin of honey samples. In case of honeys from Sorrento Peninsula, the discrimination from other Italian honeys is obtained with high accuracy. Copyright © 2010, IGI Global.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Classifcation; Geographical Discrimination; Honey; Marker Species; Support Vector Machine
Elenco autori:
Guarracino, MARIO ROSARIO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/277087
Pubblicato in:
INTERNATIONAL JOURNAL OF AGRICULTURAL AND ENVIRONMENTAL INFORMATION SYSTEMS
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-84864571535&origin=inward
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