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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/5781

Title: ANALYSIS AND DESIGN OF ASSOCIATION RULES FOR DATA MINING
Keywords: RULES, SUPPORT, CONFIDENCE, ASSOCIATION
Researcher: SACHIN
Guide(s): SHAVETA BHATIA
Registration Date: 17-1-2014
Abstract: THE PROBLEM IN KNOWLEDGE DISCOVERY IS OF INDUCING THE ASSOCIATION RULE WITHOUT MINIMUM SUPPORT THRESHOLD. THE CLASSIC APPROACH DISCOVERS THE ASSOCIATION RULES AMONG THE FREQUENTLY OBSERVED PATTERNS IN A SET OF TRANSACTION RECORDS. RESEARCHERS HAVE MOSTLY PROPOSED MODELS TO DISCOVER ASSOCIATION RULES ABOVE A MINIMUM SUPPORT THRESHOLD. WHILE SEARCHING FOR ASSOCIATION RULES AMONG FREQUENT PATTERNS IS IMPORTANT, IN SOME CASES, REPORTING THE ASSOCIATION RULES AMONG THE ITEMS THAT FALL BELOW A MINIMUM SUPPORT THRESHOLD ARE ALSO IMPORTANT. newline
Language: English
Appears in Department:Department of Computer Applications

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