Here are the slides covering chap 8 from the text by Tan et. al. chap8_basic_cluster_analysis.ppt
Here's the code that we went through in class.
kMeans Clustering: kMeans.R
Hierarchical Clustering: hclustExample.R
Here are a couple of other clustering programs that we didn't cover in class. You might be interested to see how they behave
This example runs through an affinity clustering example: apcluster.R
This example runs through a mixture model example. Mixture models can be stunningly powerful. This one correctly classifies all but 5 of the iris data - without having class labels. mclustExample.R
Homework 2
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