Intelligent Feature Extraction for Ensemble of Classifiers

Authors:
PauloV. W. Radtke;Robert Sabourin;Tony Wong
Affiliations:
Pontificia Universidade Catolica do Parana - Curitiba, Brazil;Pontificia Universidade Catolica do Parana - Curitiba, Brazil;Ecole de Technologie Superieure - Montreal, Canada
Venue:
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Year:
2005

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Abstract

This paper presents a two-level approach to create ensemble of classifiers based on intelligent feature extraction and multi-objective genetic optimization. The first stage optimizes a set of representations, which is used to create classifiers. The second stage then optimizes the ensemble's aggregated classifiers. To assess the approach's feasibility, a set of tests with isolated handwritten digits is performed. The experimental results encourage further researches in this direction, as the optimized ensemble of classifiers outperforms the single classifier approach.