Applied Clustering Techniques

Duration: 2.0 days CEU: 1.2

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-nearest-neighbor clustering, k-means clustering, hierarchical clustering, and fuzzy 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

Prerequisites

Before attending this course, you should

be able to execute SAS programs and create SAS data sets. You can gain this experience by completing the SAS Programming I: Essentials course.
have completed a graduate-level course in statistics or the Statistics II: ANOVA and Regression course.
have an understanding of matrix algebra.

Course Contents

Introduction to Clustering

types of clustering
similarity metrics

Preparation for Clustering

graphical clustering aids
initialization issues
variable clustering
cluster preprocessing

Hierarchical Clustering

hierarchical clustering methods

Partitive Clustering

k-means clustering
nonparametric clustering
fuzzy clustering

Assessing Clustering Results

determining the number of clusters
cluster profiling
scoring new observations

Software Addressed

This course addresses the following software product(s): SAS/STAT.

Classroom Course Materials

Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.

Live Web Course Materials

Students attend Live Web classes using a Web browser and a telephone and interact with their instructor and fellow classmates in real time. Each student receives an e-mail with instructions on how to join the class three business days before the class begins. The instructions e-mail includes a link to download the course materials, including the exercise files. Students need to download and print the course materials prior to class.

System Requirements

For Live Web, you must

review and follow the general system requirements.
complete the course exercises through our virtual lab. The virtual lab allows you to access the software used in class over the Internet, so that you do not need this software on your local machine.
run this test to connect to a virtual lab session. If firewall problems prevent you from connecting to the virtual lab, then you will need the following software installed and configured in your environment to participate in the course exercises:
- Base SAS 9.2 or 9.1.3 on a Windows operating system or SAS Learning Edition.
  Important: Students using SAS Learning Edition will need to create a shortcut to the SAS windowing environment (SAS Explorer, Enhanced Editor, Log, and Output windows) for use during the class. Follow these instructions for creating a shortcut to SAS prior to class.

Registration

To register for this course in the US, call 800-333-7660 or visit support.sas.com/training. This course is also available for on-site training, or you can create a custom course by combining material from several courses. For more details, contact SAS Education in Cary, NC at 919-531-7321 or send e-mail to training@sas.com.