This Applied Clustering Techniques training course covers the theoretical and practical implications of a wide array of clustering techniques that are currently available in SAS. The techniques considered include cluster preprocessing, variable clustering, k-means clustering, and hierarchical clustering.
By attending Applied Clustering Techniques workshop, delegates will learn 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
- Be able to execute SAS programs and create SAS data sets
- Knowledge in statistics
- Have an understanding of matrix algebra
The Applied Clustering Techniques class is ideal for:
- Intermediate- or senior-level statisticians, data analysts, and data miners