Resources on K Means
Aside from my tutorial (in Visual Basic Code or in Matlab code ), there are many books and journals or Internet resources discuss about K-mean 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.
- 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.
- Tapas Kanungo et al provide C++ code (for Unix, under GPL) and documentation for k-means clustering based on a combination of local search and Lloyd's algorithm (also known as the k-means algorithm).
- Matlab Statistical Toolbox contain a function name kmeans . My own Matlab code is in this page .
- kmeans is also a function in R,a free software for Statistical Computing .
- 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. .
- Cell-kmeans is an open source implementation of K-means algorithm on Cell Broadband Engine written in C
- Andrew More provides his lecture slide
- An efficient k-means clustering algorithm: Analysis and implementation (2002) by Kanungo et al
- k -Means: A new generalized k-means clustering algorithm (2003) by Yiu-Ming Cheung
- Dhillon, Guan and Kulis linkage a theoretical connection between kernel k means and spectral clustering