Volume : I, Issue : VI, March - 2012

Predictive Analysis In Data Mining Using Weighted Associative Classifier

Suwarna Gothane

Abstract :

Association rule mining is well researched techniques of data mining for expressive task, initially used in market analysis. Based on existing rules in transactional database those satisfy some minimum support and confidence constraints. Classification using Association rule mining is another major Predictive analysis technique that aims to discover a small set of rule in the database that forms an accurate classifier. Associative Classifier the combined approach that integrates association rule mining and classification rule mining called Associative Classification(AC). There are many AC approaches that have been proposed CBA, CMAR, CPAR. Proposed system introducing w–support(a new measure of itemsets) in databases. W–support introduced as frequency of itemset may not be important as it appears, because the weights of transactions are different. These weights are derived from internal structure of database based on the assumption that good transactions consist of good items. This assumption is exploited by extending Kleinberg’s HITS model(Bipartite graphs).  

Keywords :

Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Suwarna Gothane Predictive Analysis In Data Mining Using Weighted Associative Classifier Indian Journal of Applied Research, Vol.I, Issue.VI March 2012

Number of Downloads : 956

References :