Application of wrapper methods for feature selection in modelling ripening process of a viticulture crop

Authors:
Roberto Fernandez-Martinez;Julio Fernandez-Ceniceros;Andres Sanz-Garcia;Ruben Lostado-Lorza;Francisco Javier Martinezdepison-Ascacibar
Affiliations:
EDMANS research group, Department of Mechanical Engineering, University of La Rioja, Logroño, La Rioja, Spain;EDMANS research group, Department of Mechanical Engineering, University of La Rioja, Logroño, La Rioja, Spain;EDMANS research group, Department of Mechanical Engineering, University of La Rioja, Logroño, La Rioja, Spain;EDMANS research group, Department of Mechanical Engineering, University of La Rioja, Logroño, La Rioja, Spain;EDMANS research group, Department of Mechanical Engineering, University of La Rioja, Logroño, La Rioja, Spain
Venue:
ACACOS'11 Proceedings of the 10th WSEAS international conference on Applied computer and applied computational science
Year:
2011

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Abstract

The importance of final quality in agricultural products is growing ever greater, and is causing many crops to be monitored. This trend and the improvement of devices that can obtain the necessary information, make that it is stored large amount of information to work with. Apply learning algorithms in this amount of variables and data stored does that it is returned high execution times and calculation errors. To solve this problem, it is used feature reduction methods to select the most relevant information in order to reduce execution times and errors generated. Specifically, in this study, wrapper methods are used to select the most influential environmental variables during viticulture crop ripening.