Evidence Tree – Understanding the Evidence Tree P1
Understanding the Evidence Tree
Figure 1: A result with a certainty factor
Figure 2: Example evidence tree
The Evidence Tree is a visual representation of how Rainbird made a decision, broken down into fact cards about the various rules, relationships, and conditions Rainbird used to inform its decision.
In the example above, a Company, ‘ACME’ , ‘receives final decision’ about a business loan with the Decision ‘Accept’. The certainty factor of 85% has been reached by running the four conditions –
- ACME receives minimum requirements Accept
- ACME’S Credit Score Outcome: Medium
- Product selected: Credit Card
- ACME Outcome based on Registration Date: Long
- The end-user has created facts at run time by interacting with the knowledge map via a user interface (shown in red)
- Rainbird access information stored in the knowledge map (shown in orange)
- Rainbird has derived facts from rules in the knowledge map or (shown in blue),
- Imported from a datasource (shown in green, not shown in this example).
Query and Results
To see a detailed evidence tree, please run the query on the ‘receives final decision’ relationship.
Version 1.01 – Last Update: 23/02/2021