Combined Pattern Mining for D3M Using Fuzzy
S. S. Dhenakaran and S. Maheswari
DOI : 10.3844/ajassp.2013.1629.1633
American Journal of Applied Sciences
Volume 10, Issue 12
Many algorithms and models were developed but the findings are not actionable and lack of soft power while solving the complex problems. Domain Driven Data mining is used a major efforts to promote the action ability of the knowledge discovery in the real world smart decision making. Combined mining is one of the common methods for analyzing complex data for identifying complex knowledge. The deliverables of combined mining are combined patterns. The complex environment gives the combined patterns. In this research we process a new technique called Fuzzy Combined Pattern Mining (FCPM) for Domain Driven Data Mining. It was used to find all the rules that satisfy the minimum support and minimum confidence constraints. In FCPM, we first apply the fuzzy concept to find the patterns after that the fuzzy pattern will be merged to combined pattern mining. The proposed algorithm have been implemented and compared with Apriori Its performance was studied on an experimental basis. The main objective is to provide the interesting patterns to the end user. The implementation of fuzzy in combined mining will generate the rules and based on rules we can identify the interesting patterns.
© 2013 S. S. Dhenakaran and S. Maheswari. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.