Applied Clustering Techniques

Course code: CLUS51

The course looks at 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, -means clustering, and hierarchical clustering.
1 200 EUR

1 452 EUR including VAT

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Starting date: Upon request

Type: Upon request

Course duration: 14 hours

Language: en

Price without VAT: 1 200 EUR


Type Course
Language Price without VAT
Upon request Upon request 14 hours en 1 200 EUR Register
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Target group

Intermediate- or senior-level statisticians, data analysts, and data miners

Course structure

Introduction to Clustering

  • Overview.
  • Types of clustering in this course.

Preparation for Clustering

  • Sample selection.
  • Variable selection.
  • Variable standardization.
  • Graphical aids to clustering.
  • Within cluster variable transformation.

Hierarchical Clustering

  • Measuring similarity.
  • Hierarchical clustering methods.
  • Determining the number of clusters.


  • k
  • k
  • Determining the number of clusters.

Nonparametric Clustering

  • Nonparametric clustering.
  • Practices.

Cluster Profiling and Scoring

  • Cluster profiling.
  • Scoring new observations.

Appendix A: Canonical Discriminant Analysis (CDA) Plots

Appendix B: Fuzzy Clustering

Appendix C: Assessing Multivariate Normality

Appendix D: References


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 1: Essentials course.
  • Have completed a graduate-level course in statistics or the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.
  • Have an understanding of matrix algebra.
  • Do you need advice or a tailor-made course?


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