Mining Rare Itemset Based On Fp-Growth Algorithm

A Jalpa A Varsur¹, Nikul G Virpariya²

¹Student, M.E. (CSE), ²Assistant Professor, CSE Department, Gardi Vidyapith, Gujarat, India

Abstract

Frequent weighted itemset represent correlation frequently holding in data in which items may weight differently.However, in some contexts, e.g., when the need is to minimize a certain cost function, discovering rare data correlations is more interesting than mining frequent ones. Now a days, some uninteresting items are consider as important. Which are appear very less in the database. It is known as Rare or infrequent item. Finding infrequent itemset is useful in many recent field like medical, web, cloud, market basket analysis etc,. for i.e., in market basket analysis some set of items such as milk and bread customer buy frequently compared to milk and bread gold chain and ring are infrequent items. This paper takes the issue of discovering rare itemset in transaction dataset.

Keywords

• Data Mining, Frequent item, Infrequent item, Threshold, Support, Item weight

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Cite this Article as Follows

A Jalpa A Varsur, Nikul G Virpariya. "Mining Rare Itemset Based On Fp-Growth Algorithm." International Conference on Information Engineering, Management and Security (2015): 121-128. Print.