k-means algorithm
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[counter] = kMeans(numPoints, numClusters, shape, drawOn, showOn)
This function takes as inputs: numPoints: the number of random points to cluster; numClusters: the number of clusters to group the points into; shape: a string 'square', 'circle', or 'tube' to carry out the kMeans process in; drawOn: a 1 or 0 indicating whether or not to show the points dynamically joining different clusters (not suitable for more than 500 points) ; showOn: a 1 or 0 indicating whether or not to show the update in clusters as a new figure after each iteration
Given the appropriate parameters kMeans first places k = numClusters random points in the given SHAPE and then carries out the kMeans algorithm. That is, we first assign each of the N = numPoints to the initial mean which is closest (in the standard Euclidean sense), then compute the centroid/center of mass of each cluster and then begin the reassignment process again.
Eventually, the algorithm will stabilize, and plots the final clusters as well as the path that the k means have followed.
Free download from Shareware Connection - This function takes as inputs: numPoints: the number of random points to cluster; numClusters: the number of clusters to group the points into
Version: 1.0 | Size: 10 KB | Platform: Matlab, Scripts
Released Date: 11-03-2013 | Rating: 0 | Title: k-means algorithm
Author Url: http://www.mathworks.com
Program Info Url: http://www.mathworks.com
Download Url: http://www.mathworks.com/matlabcentral/fx_files/26856/1/kMeans.zip
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K-means algorithm demo - The k-means algorithm is widely used in a number applications like speech processing and image compression.
k-means++ - An efficient implementation of the k-means++ algorithm for clustering multivariate data
Overlapping K-Means - This is a variant of k-means algorithm which allows datas to belong to several clusters instead of just one.
Software implementations of PBKM - PBKM is simple and effective which can outperform the K-means algorithm.
Cloudster - Cloudster is a generic and parallel implementation of the k-means algorithm. It is written in C# and uses the Windows Azure environment.
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