BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
HoaTruong
Obsidian | Level 7

Hi,

 

I am currently working with the Link Analysis node in Enterprise Miner and would be very grateful for some guidance on interpreting the results.  I have included an example link analysis diagram to help with the discussion.  This is based on transactions made at various retailers.  My understanding is that Enterprise Miner has identified three clusters, as denoted by the red, pink and blue colour-coding.  The centre of each cluster is determined by the centrality measure selected when the link analysis node was run. 

 

I would like to understand what determines the location of each node, and the distance between nodes.  In my example, 'Ocado' is located in the upper-left of the diagram, but is positioned quite far away from its neighbours. What does this mean in terms of its relationship to other retailers within the same cluster, and to retailers in the other clusters.

 

Many thanks,

 

Hoa


Link Analysis Example.jpg
1 ACCEPTED SOLUTION

Accepted Solutions
WendyCzika
SAS Employee

The distance actually has no meaning.  The color of each node indicates the item-cluster that that node belongs to. The width of the line indicates the relative strength between two nodes.

Hope that helps,

Wendy

View solution in original post

2 REPLIES 2
WendyCzika
SAS Employee

The distance actually has no meaning.  The color of each node indicates the item-cluster that that node belongs to. The width of the line indicates the relative strength between two nodes.

Hope that helps,

Wendy

HoaTruong
Obsidian | Level 7

Thanks Wendy - much appreciated!

sas-innovate-2024.png

Available on demand!

Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.

 

Register now!

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 2 replies
  • 1759 views
  • 4 likes
  • 2 in conversation