The global k-means clustering algorithm

Pattern Recognition

Volumn 36, Issue 2, 2003, Pages 451-461

  Likas, Aristidis ^a   Vlassis, Nikos ^b   J Verbeek, Jakob ^b  

^a UNIVERSITY OF IOANNINA   (Greece)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

Clustering; Data mining; Global optimatization; k d Trees; k Means algorithm

Indexed keywords

ALGORITHMS; DATA ACQUISITION;

CLUSTER CENTER;

PATTERN RECOGNITION;

CLUSTER ANALYSIS;

EID: 0036487280     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(02)00060-2     Document Type: Article

References (13)

1. Data clustering: A review
2. An empirical comparison of four initialization methods for the k-means algorithm
3. An examination of procedures for determining the number of clusters in a data set
4. A greedy EM algorithm for Gaussian mixture learning
5. Multidimensional binary search trees used for associative searching
6. Refinements to nearest-neighbor searching in k-dimensional trees
7. Learning mixtures of Gaussians
8. A kurtosis-based dynamic approach to Gaussian mixture modeling