Aside from my tutorial (in Visual
Basic Code or in Matlab code), there are many books and journals or Internet resources
discuss about Kmean clustering, your search must be depending on your
application. Below are a few list that you may consider. I welcome any
feedback and input about other good resources that you want to include
in this list; please tell me about
it.
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Softwares/Codes
Other Tutorials
Downloadable Technical Papers
Applications
Softwares/Codes
 SPAETH2
is a collection of FORTRAN90 routines for analyzing
data by grouping into clusters which include KMEANS
 WEKA is another Data mining software under GNU public license in Java which include k means clustering. You may download the source code from Waikato university.
 Biopython project provide
tools for computational molecular biology in Python
language. The tutorial
is in here, which include kMeans
clustering module. Other k means code in Python n be found here.
 Tapas Kanungo et al provide C++
code (for Unix, under GPL) and documentation for kmeans clustering
based on a combination of local search and Lloyd's algorithm (also
known as the kmeans algorithm).
 David
J.C. MacKay give demonstration of using K mean clustering in Octave,
a free software similar to Matlab
 Matlab
Statistical Toolbox contain a function name kmeans. My own Matlab code is in this page.
 Clustan
is special commercial software for clustering.
 XLMiner™
and XLStat are both commercial software that support k mean clustering
in MS Excel
 Commercial software DTREG for modeling business also provide k means.
 Michael Eisen develop Cluster,
an open source clustering software available here implement the most
commonly used clustering methods for gene expression data analysis.
Available
for Mac, Windows and Unix.
 kmeans
is also a function in R,
a free software for Statistical Computing. More information about
k means in R software
is also available in here
 If you are using SPSS, it is also called quick
clustering, more
information is available in here
 Fuzzy c mean clustering in Matlab can be downloaded from Matlab Central File exchange
 Mathematica has kmeans function in the image processing package. You need to load teh package before using it. Clicks here for example and explanation.
 Institute for Signal and Information processing provides Java applet (with source code) of k means, PCA, LDA, SVM etc. Similarly, Jens Spehr and Simon Winkelbach also developed Java applet for k means that useful for teaching interactively.
 Kenichi Kurihara developed Bayesian k means similar to EM algorithm (code in Matlab)
 Cellkmeans is an open source implementation of Kmeans algorithm on Cell Broadband Engine written in C
 Analytics1305 is useful public cloud service machine learning technology for extremely large and complex datasets. It contains k means and other clustering techniques
 Accord.NET framework is an extension of AForge.NET, provides Machine learning of kMeans. See the tutorial of Cesar Souza on K means implementation in C#
 VLFeat contains CAPI implementation of kmeans using Lloyd and Elkan algorithm mainly used for Computer Vision
 Jose Fonseca provides k means clustering code in PHP
Other Tutorials
Downloadable Technical Papers
Applications
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