Novel Algorithm for Reduced Computational Data by Using Fuzzy Classification and Data Mining Techniques

Abstract

Fuzzy logic and Data mining is used to find out some association rules. It is very difficult to find out some association rules of fuzzy values of any membership function because fuzzy values are distinct, so it is very difficult to find the minimum frequency value of any data item sets. It also increases the operational time of item sets. So my research paper is to overcome these problems in very efficient manner. I proposes algorithm to overcome from the above mentioned problem. The size of data items is very large, so it is difficult to reduce its operational time. This research paper tries to eliminate those item sets which are not important for finding any association rule. We also try to eliminate more than 60% of item sets which is not important by using fuzzy classification technique. we able to reduce operational data. This proposed algorithm is more suitable when we apply mining association rule from very large data sets.