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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
    • Overview
    • Getting Started
    • Syntax
      • PROC FACTMAC Statement
      • AUTOTUNE Statement
      • CODE Statement
      • DISPLAY Statement
      • DISPLAYOUT Statement
      • FREQ Statement
      • ID Statement
      • INPUT Statement
      • OUTPUT Statement
      • SAVESTATE Statement
      • TARGET Statement
      • WEIGHT Statement
    • Details
    • Examples
    • References
  • 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
  • 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 FACTMAC Procedure

Overview
Getting Started
Syntax
Details
Examples
References

WEIGHT Statement

  • WEIGHT variable;

The variable in the WEIGHT statement is used as a weight to perform a weighted analysis of the data. Observations that have nonpositive or missing weights are not included in the analysis. When the WEIGHT statement is omitted, all observations that are used in the analysis are assigned a weight of 1.

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Last updated: November 11, 2020
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