Application of combining classifiers using dynamic weights to the protein secondary structure prediction – comparative analysis of fusion methods

Authors:
Tomasz Woloszynski;Marek Kurzynski
Affiliations:
Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland;Faculty of Electronics, Chair of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland
Venue:
ISBMDA'06 Proceedings of the 7th international conference on Biological and Medical Data Analysis
Year:
2006

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Abstract

We introduce common framework for classifiers fusion methods using dynamic weights in decision making process. Both weighted average combiners with dynamic weights and combiners which dynamically estimate local competence are considered. Few algorithms presented in the literature are shown in accordance with our model. In addition we propose two new methods for combining classifiers. The problem of protein secondary structure prediction was selected as a benchmark test. Experiments were carried out on previously prepared dataset of non-homologous proteins for fusion algorithms comparison. The results have proved that developed framework generalizes dynamic weighting approaches and should be further investigated.