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Title: Artificial Intelligence/Machine Learning - k-means clustering tutorial Introduction to k-means clustering, a popular data mining and unsupervised learning algorithm. Free code, software, resources and examples are available for download.
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K-Mean Clustering Tutorial
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K-Mean Clustering Tutorials
By Kardi Teknomo, PhD.
This tutorial will introduce you to the heart of Pattern
Recognition, unsupervised learning of Neural network called k-means
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.
What is K-Mean
Clustering?
Numerical Example (hand calculation)
How the
K-Mean Clustering algorithm works?
Download
Code in VB (Screenshot)
Download code in Matlab
What is the mimimum number of attributes?
What are
the applications of K-mean clustering?
What are
the weaknesses of K-Mean Clustering?
Are there
any other resources for K-mean Clustering?
Citation
(other papers that has reference to this tutorial)
Comments
for this tutorial
See also: Similarity and Dissmilarity Measurements (for multivariate distances) Discriminant Analysis (LDA), K Nearest Neighbor
Share and save this tutorial
This tutorial is copyrighted.
Preferable reference for this tutorial is
Teknomo, Kardi. K-Means Clustering Tutorials. http:\\people.revoledu.com\kardi\
tutorial\kMean\
© 2006 Kardi Teknomo. All Rights Reserved.
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Introduction | to | k-means | clustering, | a | popular | data | mining | and | unsupervised | learning | algorithm. | | Free | code, | software, | resources | and | examples | are | available | for | download. |
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http://people.revoledu.com/kardi/tutorial/kMean/index.html
k-means clustering tutorial 2008 September
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Introduction to k-means clustering, a popular data mining and unsupervised learning algorithm. Free code, software, resources and examples are available for download.
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