Seed based fuzzy decision reduct for hybrid decision systems

Fuzzy rough sets is an extension to classical rough sets. The fuzzy rough set model is useful in feature selection for hybrid decision systems. Fuzzy decision reduct uses Radzikowska´s Fuzzy Rough Set model for feature selection in hybrid decision systems. The computational complexity of fuzzy decision reduct computation makes it not suitable for large hybrid decision systems. In this paper, an approach is developed for computing fuzzy decision reduct by seed reduct using a suitable discretization of quantitative conditional attributes. Fuzzy decision reduct is computed for original decision system by evolving over seed reduct. Theoretical analysis and experimental results on benchmark decision systems validate that the method has achieved significant computational gains over normal approach without loss of classification accuracy.