Applying UChooBoost algorithm in precision agriculture

Authors:
Anastasiya Kolesnikova;Chi-Hwa Song;Won Don Lee
Affiliations:
Chungnam National University, Daejeon, Korea;Chungnam National University, Daejeon, Korea;Chungnam National University, Daejeon, Korea
Venue:
Proceedings of the International Conference on Advances in Computing, Communication and Control
Year:
2009

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Abstract

Informatization is primary characteristic of current agriculture stage. Precision Agriculture is destination of new technologies and principles in agriculture using digital information. We consider data analysis as an aspect of Precision Agriculture and introduce UChooBoost applied to classification problem in agriculture. UChooBoost is a supervised learning ensemble-based algorithm for extended data, based on bootstrap technique. UChoo classifier is used as Weak Learner. Combining hypotheses by new weighted majority voting developed for extended results expression allows UChooBoost to achieve better performance level.