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k*-Means — A Generalized k-Means Clustering Algorithm with Unknown Cluster Number

2002
This paper presents a new clustering technique named STepwise Automatic Rival-penalized (STAR) k-means algorithm (denoted as k*-means), which is actually a generalized version of the conventional k-means (MacQueen 1967). Not only is this new algorithm applicable to ellipse-shaped data clusters rather than just to ball-shaped ones like the k-means ...
openaire   +1 more source

Clustering by k-means

2009
Clustering techniques are used for finding suitable groupings of samples belonging to a given set of data. There is no knowledge a priori about these data. Therefore, such set of samples cannot be considered as a training set, and classification techniques cannot be used in this case.
Antonio Mucherino   +2 more
openaire   +1 more source

Collaborative annealing power k-means++ clustering

Knowledge-Based Systems, 2022
Hongzong LI, Jun Wang
exaly  

The global k-means clustering algorithm

Pattern Recognition, 2003
Aristidis Likas, Nikos Vlassis
exaly  

Automated variable weighting in k-means type clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
Joshua Huang, Michael Ng
exaly  

An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data

IEEE Transactions on Knowledge and Data Engineering, 2007
Michael Ng, Joshua Huang
exaly  

TW-k-means: Automated two-level variable weighting clustering algorithm for multiview data

IEEE Transactions on Knowledge and Data Engineering, 2013
Xiaojun Chen, Yunming Ye, Joshua Huang
exaly  

K-Means Clustering Versus Validation Measures: A Data-Distribution Perspective

IEEE Transactions on Systems, Man, and Cybernetics, 2009
Junjie Wu, Jian Chen
exaly  

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