Using significant, positively associated and relatively class correlated rules for associative classification of imbalanced datasets

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2007, Pages 679-684

  Verhein, Florian ^a   Chawla, Sanjay ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULE MINING; ASSOCIATIVE CLASSIFICATION; ASSOCIATIVE CLASSIFIERS; CLASSIFICATION QUALITY; COMPUTATIONALLY EFFICIENT; CORRELATED RULES; CORRELATION RATIO; DATA-SETS; FRAUD DETECTION; IMBALANCED DATA SETS; INTERNATIONAL CONFERENCES; MEDICAL DIAGNOSIS; RULE BASE; RULE-BASED; RULE-BASED CLASSIFIERS; STATISTICAL TECHNIQUES;

ADMINISTRATIVE DATA PROCESSING; ASSOCIATIVE PROCESSING; CLASSIFIERS; DATA MINING; DECISION SUPPORT SYSTEMS; DIAGNOSIS; FEATURE EXTRACTION; INFORMATION MANAGEMENT; LAWS AND LEGISLATION; LEARNING SYSTEMS; MINING; SEARCH ENGINES; STATISTICAL METHODS;

CLASSIFICATION (OF INFORMATION);

EID: 49749113225     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2007.63     Document Type: Conference Paper

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