Combining Evolutionary, Connectionist, and Fuzzy Classification Algorithms for Shape Analysis

Authors:
Paul L. Rosin;Henry O. Nyongesa
Affiliations:
-;-
Venue:
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Year:
2000

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Abstract

This paper presents an investigation into the classification of a dificult data set containing large intra-class variability but low interclass variability. Standard classifiers are weak and fail to achieve satisfactory results however, it is proposed that a combination of such weak classifiers can improve overall performance. The paper also introduces a novel evolutionary approach to fuzzy rule generation for classification problems.