Message Tracing and Model Debugging

Message Tracing

Models aren't the real world, they are imperfect descriptions of the real world which are good enough for the purpose at hand. Often they are good enough to make useful predictions, but sometimes they exhibit surprising behavior. In those cases, we would like to isolate where that behavior comes from. Models, like computer programs, often need to be "Debugged".

In the Shafer and Shenoy algorithm, used by Graphical-Belief, probabilities (or beliefs) are calculated by passing messages through the junction tree. Graphical-Belief allows you to select any node or edge in the tree and see the messages passing through the corresponding node in the junction tree. This has proved an invaluable tool for debugging models. (Almond [1995a] provides a detailed example in which an anomalous behavior is found to be cause by counting the same evidence twice.)

Evidence Flows

Madigan, Mosurski and Almond [1996] suggest showing evidence flow by coloring the arrows. In this scheme, the inner width of the arrow represents the actual or expect weight of evidence each node provides for the next from that node, while the outer width represents the potential weight of evidence (the maximum weight of evidence over all possible instantiations of that node). The inner bar is colored red or blue according to whether the evidence is positive or negative.

The figure above illustrates the difficulty with this scheme. Look closely at the two evidence chains (in both cases X-5 supplies the evidence and X-1 is the target) and try and determine where the difference lies. As we felt that interpreting evidence chains would require too much analyst training, we never fully incorporated them into Graphical-Belief.

Where to go from here

If you have been faithfully following the linear path through this web site, you have now reached the end of the example section. If you still want more information about Graphical-Belief, you can download some technical reports or look into getting a beta test license. For any questions which are not covered there, you can send me email at almond@acm.org.

Thank you for your perserverance.

Explanation Return to the beginning of the explanation examples.

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View a list of Graphical-Belief in publications and downloadable technical reports.

The Graphical-Belief user interface is implemented in Garnet.

Get more information about obtaining Graphical-Belief (and why it is not generally available).

get the home page for Russell Almond , author of Graphical-Belief.

Click here to get to the home page for Insightful (the company that StatSci has eventually evolved into).

Russell Almond, <lastname> (at) acm.org

Last modified: Tue Aug 20 11:39:02 1996