Abstract
The large collection of formal concepts can be a hedge of the application of FCA. Development of methods which help to overcome the problem of the huge size of concept lattice is thus an important task. This paper proposes clustering-based reduction algorithm for reducing the size of fuzzy concept lattices. At the end, experiment results show that the compression rate of the concept lattice and classifier is remarkable, while it preserves the accuracy of classification of concept lattice.
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