Learning with ensemble of linear perceptrons

Authors:
Pitoyo Hartono;Shuji Hashimoto
Affiliations:
Future University-Hakodate, Hakodate City, Japan;Waseda University, Tokyo, Japan
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

In this paper we introduce a model of ensemble of linear perceptrons. The objective of the ensemble is to automatically divide the feature space into several regions and assign one ensemble member into each region and training the member to develop an expertise within the region. Utilizing the proposed ensemble model, the learning difficulty of each member can be reduced, thus achieving faster learning while guaranteeing the overall performance.