Applying a hybrid data-mining approach to prediction problems: A case of preferred suppliers prediction

International Journal of Production Research

Volumn 44, Issue 14, 2006, Pages 2935-2954

  Tseng, T L ^a   Huang, C C ^b   Jiang, F ^c   Ho, J C ^d  

^a UNIVERSITY OF TEXAS AT EL PASO   (United States)

^b NATIONAL CHI NAN UNIVERSITY   (Taiwan)

^c GEORGIA STATE UNIVERSITY   (United States)

^d Columbus State University   (United States)

Author keywords

Feature selection; Negative information; Preferred suppliers prediction; Rough set theory; Support vector machines

Indexed keywords

DATABASE SYSTEMS; DECISION MAKING; INFORMATION RETRIEVAL; MATHEMATICAL MODELS; PROBLEM SOLVING; RANDOM PROCESSES; ROUGH SET THEORY;

FEATURE SELECTION; NEGATIVE INFORMATION; PREFERRED SUPPLIERS PREDICTION; SUPPORT VECTOR MACHINES (SVM);

DATA MINING;

EID: 33744986720     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207540600654525     Document Type: Article

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