A fuzzy k-prototype clustering algorithm for mixed numeric and categorical data

Knowledge-Based Systems

Volumn 30, Issue , 2012, Pages 129-135

  Ji, Jinchao ^a   Pang, Wei ^a,b   Zhou, Chunguang ^a   Han, Xiao ^a   Wang, Zhe ^a  

^a JILIN UNIVERSITY   (China)

^b UNIVERSITY OF ABERDEEN   (United Kingdom)

Author keywords

Attribute significance; Data mining; Dissimilarity measure; Fuzzy clustering; Mixed data

Indexed keywords

ATTRIBUTE SIGNIFICANCE; CATEGORICAL DATA; CATEGORICAL FEATURES; CLUSTERING PROCESS; CO-OCCURRENCE; DATA OBJECTS; DISSIMILARITY MEASURES; FUZZY CENTROID; K-PROTOTYPE; MISCLASSIFICATIONS; MIXED DATA; REAL-WORLD DATASETS; TRADITIONAL CLUSTERING;

ARTIFICIAL INTELLIGENCE; DATA MINING; FUZZY CLUSTERING; SOFTWARE ENGINEERING;

CLUSTERING ALGORITHMS;

EID: 84862800691     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.01.006     Document Type: Article

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