Week 1: Course introduction, data mining overview, clustering

Lecture 1 slides

Lecture 2 slides: Clustering (courtesy Professor Kumar and Mahesh Joshi at Minnesota)

Professor Kumar has also done a more detailed treatment of K-Means clustering, slides are available here.

Suggested Reading

Browse the ACM Communications Special Issue on Data Mining: Communications of the ACM 39(11), November 1996. Pay particular attention to the article by Usama Fayyad, Gregory Piatetsky-Shapiro and Padhraic Smyth, ``The KDD process for extracting useful knowledge from volumes of data'', pp. 24-26.

Let me know if you have trouble getting the article - I thought we were site-licensed for the ACM digital library, but access seems to require a password. If you are an ACM member, your standard ACM account/password will allow you access to Communications.

I couldn't find a good article on Self-Organizing Maps available on-line. There is a reasonable treatment available as part of Samuel Kaski's thesis - he was a student of Professor Kohonen.


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