Novel Algorithm to Reduced Computational Data Sets for Fuzzy Association Rule
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 9
Abstract
The Data Mining Association rule is suitable for small or medium scale data sets. For large data sets it becomes more complex because while applying association rule finding candidate and large item set again and again amongst variables. So we reduce the computational time or data complexity by applying the proposed algorithm. The large data set requires more computational time on data operations. If we apply fuzzy association rule then it becomes a complex task. So it is necessary to reduce the large data set into smaller data set by applying the proposed Novel Algorithm. After that we can apply a fuzzy association rule. We work on reduction of unwanted data sets from large data sets that are not important for making the decision. This research paper tries to eliminate those item sets which are not important for finding any association rule. We apply our pseudo code or algorithm to achieve our task.
Authors and Affiliations
Rohit Miri, Priyanka Tripathi, Keshri Verma, S. R. Tandan
Keywords
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