Applied Clustering Techniques
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Applied Clustering Techniques
Duration: 14 hours
CLUS : CLUS51
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 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.
  • SAS Products Covered
    SAS/STAT
    Course Outline
    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-Means Clustering
  • The k-means clustering algorithm.
  • k-means clustering using the FASTCLUS procedure.
  • 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

    Live Instructor Dates SOLD SEPARATELY
    DATES ▼ LOCATION
    TIME
    LANGUAGEEVENT FEE
    24-27 JUN 2025Live Web, US10:30 AM-2:30 PM EDTSpanish2,000 USD


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