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SAS® Viya® Programming Documentation
2021.1.2
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This documentation is for a version of the software that is not covered by Standard Support. Select a different version from the version selector in the banner, or access the latest documentation.
  • Welcome to SAS Programming Documentation
  • What's New
  • Learning SAS Viya
  • Syntax Quick Links
  • Advanced Analytics
    • Data Mining and Machine Learning
      • SAS Visual Data Mining and Machine Learning
        • Getting Started with SAS Visual Data Mining and Machine Learning
        • Data Mining and Machine Learning Procedures
        • Data Mining and Machine Learning: The NETWORK Procedure
          • Introduction
          • The NETWORK Procedure
            • Overview
            • Getting Started
            • Syntax
            • Details
            • Examples
            • References
        • SAS Visual Data Mining and Machine Learning Programming Guide
        • SAS Deep Learning Programming Guide
        • SAS Reinforcement Learning Programming Guide
    • Econometrics
    • SAS Enterprise Miner: High-Performance Procedures
    • Forecasting
    • IML (Interactive Matrix Language)
    • Optimization and Simulation
    • Quality Control
    • Statistics
    • Text Analytics
  • Data Access
  • Cloud Analytic Services
  • SAS Language Reference
  • Migrating to UTF-8
  • Example Data Sets
  • SAS Code Debugging
  • Output and Graphics
  • In-Database Technology
  • Security and Administration
  • SAS Servers
  • Using the batch Plug-In for the SAS Viya CLI
  • SAS Data Quality
  • SAS Job Execution Web Application
  • SAS Visual Analytics
  • SAS Viya: Administration
  • SAS Viya Operations
  • SAS Studio
  • Other Resources
Data Mining and Machine Learning: The NETWORK Procedure
 

The NETWORK Procedure

Overview
Getting Started
Syntax
Details
Examples
References

Examples: NETWORK Procedure

Subsections:
  • 2.1 Articulation Points in a Terrorist Network
  • 2.2 Influence Centrality for Project Groups in a Research Department
  • 2.3 Betweenness and Closeness Centrality for Computer Network Topology
  • 2.4 Betweenness and Closeness Centrality for Project Groups in a Research Department
  • 2.5 Eigenvector Centrality for Word Sense Disambiguation
  • 2.6 Community Detection on Zachary’s Karate Club Data
  • 2.7 Recursive Community Detection on Zachary’s Karate Club Data
  • 2.8 Centrality Metrics for an Undirected Graph by Community
  • 2.9 Cycle Enumeration for Kidney Donor Exchange
  • 2.10 Transitive Closure for Identification of Circular Dependencies in a Bug Tracking System
  • 2.11 Reach Networks for Computing the Market Coverage of a Terrorist Network
  • 2.12 Connected Components for US Patent Citations
  • 2.13 Shortest Paths of the New York Road Network
  • 2.14 Shortest Path in a Road Network by Date and Time
  • 2.15 Pattern Matching in a Social Network
  • 2.16 Detection of Value-Added Tax Carousel Fraud
  • 2.17 Node Similarity for Link Prediction
  • 2.18 A Node Similarity Recipe Recommendation Engine
  • 2.19 Node Embeddings for Zachary’s Karate Club Data
  • 2.20 Node Embeddings for European Roads Data
  • 2.21 Learning Word Embeddings from Synonym Pairs
  • 2.22 Using Projection to Recommend Recipe Ingredient Pairings
Last updated: June 11, 2021
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