Database Reference
In-Depth Information
If we look at a graph of the results, we can see that the results are very similar to what
K-Means clustering produced. Actually, there's only one data point that was classiied
differently, which I've highlighted. In this case, hierarchical clustering grouped that data
point incorrectly, possibly pairing it with one of the points to its right:
Like K-Means clustering, hierarchical clustering is based on a distance measurement, so it will
also have trouble correctly classifying data points along the margins between two groups with
close, non-distinct data points.
There's more…
F
The documentation for the
HierarchicalClusterer
at
http://weka.
sourceforge.net/doc.dev/weka/clusterers/HierarchicalClusterer.
html
has more information about the options available for this algorithm
F
Wikipedia has a good introduction to hierarchical clustering at
F
David Blei has a set of slides that provides another excellent summary of this
algorithm, at
http://www.cs.princeton.edu/courses/archive/spr08/
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The topic,
Introduction to Information Retrieval
, also has a more in-depth look at
hierarchical clustering. You can ind it online at
http://nlp.stanford.edu/IR-
