IRW-2007-11: The K-Means Algorithm

By now, current subscribers should have received the November issue of IR Watch - The Newsletter. The following topics are covered:

Introduction

The K-Means Algorithm

Applications

Clustering by Features

K-Means Example

The Sum of Squared Error (SSE)

Selecting a Stopping Condition

Clustering by Cosine Similarities

The Initial Centroid Problem

Bisecting K-Means

Limitations of K-Means

From K-Means to K-Medoids

K-Means and Scaling

From Spherical K-Means to Fractal Clusters

Conclusion

News, Research, and Events

Terms of Use and Copyright

If you are working in this area, this issue will help you a lot. I’m currently advising a grad student working on a K-Means graduate project at the MS level and he found the issue really useful. If you are new to the topic, the material discussed also serves as a handy tutorial.