Clustering is the  process of breaking down a large population that has a high degree of variation and noise into smaller groups with lower variation. It is a popular data mining activity. In a poll conducted by Kdnuggets, clustering was voted as the 3rd most frequently used data mining technique in 2011. Only decision trees and regression got more votes.

Cluster analysis is an important part of an analyst’s arsenal. One needs to master this technique as it is going to be used often in business situations. Some common applications of clustering are –

  1. Clustering customer behavior data for segmentation
  2. Clustering transaction data for fraud analysis in financial services
  3. Clustering call data to identify unusual patterns
  4. Clustering call-centre data to identify outlier performers (high and low)

Agenda for the clustering session

[youtube]http://www.youtube.com/watch?v=zB181gRwbF8[/youtube]
We recently posted some videos on clustering. Please do let us know if you find them useful.

Introduction to Clustering

[youtube]http://www.youtube.com/watch?v=zqKFH7WNmfE[/youtube]

How does k-means work?

[youtube]http://www.youtube.com/watch?v=aiJ8II94qck[/youtube]

 

Interested in learning about other Analytics and Big Data tools and techniques? Click on our course links and explore more.
Jigsaw’s Data Science with SAS Course – click here.
Jigsaw’s Data Science with R Course – click here.

Jigsaw’s Big Data Course – click here.
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