alexa AN IMPROVED ASSOCIATION RULE MINING WITH FP TREE USING
ISSN: 1948-1432

Journal of Global Research in Computer Sciences
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Research Article

AN IMPROVED ASSOCIATION RULE MINING WITH FP TREE USING POSITIVE AND NEGATIVE INTEGRATION

Rashmi Shikhariya*1 and Prof. Nitin Shukla2
  1. Computer Science & Engineering Shri Ram Institute of Technology Jabalpur, India
  2. Computer Science & Engineering Shri Ram Institute of Technology Jabalpur, India
Corresponding Author: Rashmi Shikhariya, E-mail: [email protected]
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Abstract

Construction and development of classifier that work with more accuracy and perform efficiently for large database is one of the key task of data mining techniques [l7] [18]. Training dataset repeatedly produces massive amount of rules. It‟s very tough to store, retrieve, prune, and sort a huge number of rules proficiently before applying to a classifier[1]. In such situation FP is the best choice but problem with this approach is that it generates redundant FP Tree. A Frequent Pattern Tree (FP-Tree) is a type of prefix tree [3] that allows the detection of recurrent (frequent) item set exclusive of the candidate item set generation [14]. It is anticipated to recuperate the flaw of existing mining methods. FP –Trees pursues the divide and conquers tactic. In this paper we have adopt the same idea of author [17] to deal with large database. For this we have integrated a positive and negative rule mining concept with frequent pattern (FP) of classification. Our method performs well and produces unique rules without ambiguity.

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