3 dimensional Frequent Closed Pattern miner

Frequent Closed Pattern mining has been an important step in data mining research. This paper introduces an algorithm to deal with problem of finding frequent closed pattern from a given 3 dimensional periodical set of data. The miner works on zero removal principle to generate generators. Generators use a tree based approach to mine frequent closed pattern (FCP). To filter each newly generated node in tree, three tests are adopted 1) SRT 2) IRT 3) TVT. Nodes which pass tests are expanded further. Results obtained from mining of all filtered independent subtrees shows all FCPs present in transactions.