Quantitative evaluation of approximate frequent pattern mining algorithms

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2008, Pages 301-309

  Gupta, Rohit ^a   Fang, Gang ^a   Field, Blayne ^b   Steinbach, Michael ^a   Kumar, Vipin ^a  

^a UNIVERSITY OF MINNESOTA   (United States)

^b University of Wisconsin   (United States)

Author keywords

Approximate frequent itemsets; Association analysis; Error tolerance; Quantitative evaluation

Indexed keywords

APPROXIMATE FREQUENT ITEMSETS; ASSOCIATION ANALYSIS; ASSOCIATION MININGS; COMPREHENSIVE EVALUATIONS; DATA SETS; ERROR THRESHOLDS; ERROR TOLERANCE; EVALUATION FRAMEWORKS; FREQUENT ITEMSET; FREQUENT PATTERN MININGS; ITEM SETS; OPTIMAL PARAMETERS; PATTERN MINING ALGORITHMS; POST-PROCESSING; QUANTITATIVE APPROACHES; QUANTITATIVE EVALUATION; RANDOM NOISE; REAL-LIFE DATA SETS; SOURCE CODES; SYNTHETIC DATA SETS;

ALGORITHMS; DATA MINING; INFORMATION MANAGEMENT; MINING; RANDOM ERRORS;

PARAMETER ESTIMATION;

EID: 65449186692     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1401890.1401930     Document Type: Conference Paper

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