Evaluation of Adaptive FRIFS Method through Several Classification Comparisons

International audienceAn iterative method to select suitable features for pattern recognition context has been proposed (FRIFS). It combines a global feature selection method based on the Choquet integral and a fuzzy linguistic rule classifier. In this paper, enhancements of this method are presented. An automatic step has been added to make it adaptive to process numerous features. The experimental study, made in a wood defect recognition context, is based on several classifier result analysis. They show the relevancy of the remaining set of selected features. The recognition rates are also considered for each class separately, showing the good behavior of the proposed method

Fuzzy Rule Iterative Feature Selection (FRIFS) with Respect to the Choquet Integral Apply to Fabric Defect Recognition

ISBN 0.7803.9489.5International audienceAn iterative method to select suitable features in an industrial fabric defect recognition context is proposed in this paper. It combines a global feature selection method based on the Choquet integral and a fuzzy linguistic rule classifier. The experimental study shows the wanted behaviour of this approach: the feature number decreases whereas the recognition rate increases. Thus, the number of generated fuzzy rules is reduced