bayesia logo

Edit Forbidden Arcs — Add/Remove

Usage

  • The Add button brings up a dialog box in which you can define constraints on arcs:

  • Here, you can specify precisely what types of arcs should be forbidden.

  • You can specify constraints for individual nodes and classes or create meta constraints that apply to groups of nodes and classes.

  • This provides for an enormous number of possible configurations, of which we now illustrate a small selection of constraints.

  • We use the following fully connected network as a starting point for showing the effects of applying Forbidden Arcs. While a fully connected network is rarely feasible (or useful) if you have more than a few nodes, here, it can highlight the absence of arcs due to the Forbidden Arc constraints.

  • There are many ways you can define individual Forbidden Arcs or define sets of Forbidden Arcs in the Forbidden Arc Editor, for instance:

    • Between a node and another node: N1 — N2
      N1 — N2
    • Between a node and all other nodes: N1 — <All Nodes>
      N1 — \<All Nodes\>
    • Between a node and a class: N1 — Class A
      N1 — Class A
    • Between two classes: Class A — Class B
      Class A — Class B
    • Between nodes of the same classes (intra-class): <Same Class> — <Same Class>
      \<Same Class\> — \<Same Class\>
    • Between nodes of different classes (inter-class): <Different Class> — <Different Class>
      \<Different Class\> — \<Different Class\>
    • Between classes and each of the classes: <Each Class> — <Each Class>
      \<Each Class\> — \<Each Class\> — \<Different Class\>
    • Between nodes and each of the classes: Class A — <Each Class>
      Class A — \<Each Class\>
  • Furthermore, you can specify which arc orientations are prohibited:

    • Prevent the arc from the node/class in the Start column to the node/class in the End column (→)
    • Prevent the arc in both directions (—)

Workflow Animation

  • This animation shows how we add a random selection of constraints and then perform Unsupervised Learning using the EQ Algorithm with a Structural Coefficient of 0.
  • Without Forbidden Arcs, this structural learning process would produce a fully-connected network with 21 arcs.
  • Given all the Forbidden Arcs we specified, we obtain, after learning, a much simpler network with only six arcs.
⚠️

Note that defining a Forbidden Arc — after the fact — on a machine-learned network, will not modify that network. The arc prohibition would only become relevant when you perform learning again.


Copyright © 2024 Bayesia S.A.S., Bayesia USA, LLC, and Bayesia Singapore Pte. Ltd. All Rights Reserved.