A hybrid AIS-SVM ensemble approach for text classification

Authors:
Mário Antunes;Catarina Silva;Bernardete Ribeiro;Manuel Correia
Affiliations:
School of Technology and Management, Polytechnic Institute of Leiria and Faculty of Science, University of Porto, Center for Research in Advanced Computing Systems, Portugal;School of Technology and Management, Polytechnic Institute of Leiria, Portugal and Department of Informatics Engineering, Center for Informatics and Systems of the University of Coimbra, Portugal;Department of Informatics Engineering, Center for Informatics and Systems of the University of Coimbra, Portugal;Faculty of Science, University of Porto, Center for Research in Advanced Computing Systems, Portugal
Venue:
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Year:
2011

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Abstract

In this paper we propose and analyse methods for expanding state-of-the-art performance on text classification. We put forward an ensemble-based structure that includes Support Vector Machines (SVM) andArtificial Immune Systems (AIS).The underpinning idea is thatSVMlike approaches can be enhanced with AIS approaches which can capture dynamics in models. While having radically different genesis, and probably because of that, SVM and AIS can cooperate in a committee setting, using a heterogeneous ensemble to improve overall performance, including a confidence on each system classification as the differentiating factor. Results on the well-known Reuters-21578 benchmark are presented, showing promising classification performance gains, resulting in a classification that improves upon all baseline contributors of the ensemble committee.