The course looks at the theoretical and practical implications of a wide array of clustering techniques currently available in SAS. The techniques considered include cluster preprocessing, variable clustering, k-means clustering, and hierarchical clustering.
Learn how to
- prepare and explore data for a cluster analysis
- distinguish among many different clustering techniques, making informed choices about which to use
- evaluate the results of a cluster analysis
- determine the appropriate number of clusters to retain
- profile and describe clustered observations
- score observations into clusters.
Who should attend
Intermediate or senior level statisticians, data analysts, and data miners
Before attending this course, you should
This course addresses SAS/STAT software.