Concept lattice reduction using attribute inference

Formal Concept Analysis (FCA) Is a data analysis method and it outputs a concept structure called a concept lattice. One of the problems of FCA is that the size of a concept lattice becomes far larger as data become larger. Various methods for reducing a concept lattice have been proposed, but they have disadvantage, e.g. reduced one is not a lattice. In this paper, we propose a method for reduction using attribute inference based on an approximate implication. We also evaluated some methods regarding that a reduced lattice has noise.