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SAS® Visual Data Mining and Machine Learning: Procedures
2020.1
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  • Introduction
  • Shared Concepts
  • The ASTORE Procedure
  • The BNET Procedure
  • The BOOLRULE Procedure
  • The FACTMAC Procedure
  • The FASTKNN Procedure
  • The FISM Procedure
  • The FOREST Procedure
  • The GMM Procedure
  • The GRADBOOST Procedure
  • The GVARCLUS Procedure
  • The KPCA Procedure
  • The MBANALYSIS Procedure
  • The MTLEARN Procedure
  • The MWPCA Procedure
    • Overview
    • Getting Started
    • Syntax
    • Details
    • Examples
    • References
  • The NNET Procedure
  • The OPTBINNING Procedure
  • The RPCA Procedure
  • The SEMISUPLEARN Procedure
  • The SPARSEML Procedure
  • The SVDD Procedure
  • The SVMACHINE Procedure
  • The TEXTMINE Procedure
  • The TMSCORE Procedure
  • The TSNE Procedure
 

The MWPCA Procedure

Overview
Getting Started
Syntax
Details
Examples
References

Examples: MWPCA Procedure

Subsections:
  • 16.1 Anomaly Detection of Parking Lot Floodlights

Note: Input data must be in a CAS table that is accessible in your CAS session. You must refer to this table by using a two-level name. The first level must be a CAS engine libref, and the second level must be the table name. For more information, see the sections Using CAS Sessions and CAS Engine Librefs and Loading a SAS Data Set onto a CAS Server in Chapter 2, Shared Concepts.

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Last updated: November 11, 2020
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