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SAS Enterprise Miner: High-Performance Procedures
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  • Credits and Acknowledgments
  • Introduction
  • Shared Concepts and Topics
  • The HP4SCORE Procedure
  • The HPBNET Procedure
  • The HPCLUS Procedure
  • The HPDECIDE Procedure
  • The HPFOREST Procedure
    • Overview: HPFOREST Procedure
    • Getting Started: HPFOREST Procedure
    • Syntax: HPFOREST Procedure
    • Details: HPFOREST Procedure
      • Bagging the Data
      • Training a Decision Tree
      • Controlling for Variable Selection Bias
      • Selecting a Splitting Variable
      • Searching for a Splitting Rule
      • Pruning
      • Predicting an Observation
      • Measuring Prediction Error
      • Adjusting Statistics When Sampling Target Classes Unevenly
      • Handling Missing Values
      • Handling Values That Are Absent from Training Data
      • Modeling Incremental Response from a Treatment
      • Increasing Accuracy by Increasing Tree Size
      • Using Distributed Data Wisely
      • Measuring Variable Importance
      • Displaying the Output
      • ODS Table Names
    • Examples: HPFOREST Procedure
    • References
  • The HPNEURAL Procedure
  • The HPREDUCE Procedure
  • The HPSVM Procedure
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