By Kardi Teknomo, PhD.
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This tutorial will introduce you to the heart of Pattern
Recognition, unsupervised learning of Neural network called kmeans
clutering. When User click picture box to input new data (X,Y), the
program will make group/cluster the data by minimizing the sum of squares
of distances between data and the corresponding cluster centroids. Different
color code represent the clusters. This algorithm is a standard and
popular algorithm for unsupervised learning of Neural network, Pattern
recognitions, Classification analysis, clustering analysis etc.
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Topics of this k means tutorials:
What is KMean Clustering?
Numerical Example (hand calculation); Spanish translation available here
How the KMean Clustering algorithm works?
Download Code in VB (Screenshot)
Download code in Matlab
What is the mimimum number of attributes?
What are the applications of Kmean clustering?
What are the weaknesses of KMean Clustering?
Are there any other resources for Kmean Clustering?
Citation (other papers that has reference to this tutorial)
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See also:
Similarity and Dissmilarity Measurements (for multivariate distances)
Discriminant Analysis (LDA)
K Nearest Neighbor
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This tutorial is copyrighted.
Preferable reference for this tutorial is
Teknomo, Kardi. KMeans Clustering Tutorials. http:\\people.revoledu.com\kardi\
tutorial\kMean\
