Direct discriminative pattern mining for effective classification

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2008, Pages 169-178

  Cheng, Hong ^a   Yan, Xifeng ^b   Han, Jiawei ^a   Yu, Philip S ^c  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

^c UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; TECHNOLOGY;

ASSOCIATIVE CLASSIFICATION; CLASSIFICATION ACCURACIES; CLASSIFICATION RULES; COMPUTATIONALLY EXPENSIVE; DATA ENGINEERING; EMPIRICAL RESULTS; FEATURE SELECTION; FP TREES; FREQUENT PATTERN MINING; FREQUENT PATTERNS; INTERNATIONAL CONFERENCES; MINIMUM SUPPORT; MINING PROCESSING; ORDERS-OF-MAGNITUDE; PATTERN MINING; PATTERN SETS; PROBLEM SIZES; TRAINING INSTANCES; TWO-STEP APPROACH; TWO-STEP PROCESSES;

MINING;

EID: 52649163329     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDE.2008.4497425     Document Type: Conference Paper

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