1. Evaluation of Bayesian Networks Used for Diagnostics[1]
K. Wojtek Przytula: HRL Laboratories
Denver Dash: University of Pittsburgh
Don Thompson: Pepperdine University

2. DIAGNOSIS SUPPORT TOOL
DIAGNOSIS - MODEL BASED APPROACH
APPLICATION DOMAIN
DOMAIN MODEL
TROUBLESHOOTER
DIAGNOSIS SUPPORT TOOL
QUERY
DECISION

3. Bayesian Network Diagnostics
Bayesian Networks as models for computerized diagnostic assistants
Model evaluation has not been addressed
Model quality determines diagnosis quality
Evaluation provides a basis for model performance estimation

4. GRAPHICAL MODEL FOR DIAGNOSIS (GRAPH AND PROBABILITY THEORY)
GRAPH (structure):
Two Fault Nodes: F1, F2.
Three Observation Nodes – e.g. symptoms and tests.
Causal Links
PROBABILITIES (parameters)
Prior Probabilities of Faults
Conditional Probabilities of Observations given Faults
The Model constitutes a joint probability distribution over the nodes.
It is obtained from data or knowledge or both.

5. Bayesian Network for Example of Car Diagnostics

6. Bayesian Network Evaluation]
Using Inference, Monte Carlo Simulation, & Visualization Techniques
Step 1
Set Defective Component
Execute Forward Inference
Step 2
Sample Observation States
Execute Reverse Inference

7. Forward Inference

8. Reverse Inference

9. Evaluation Conclusions
Identification of Critical Elements Responsible for Incorrect Diagnosis
Components with weak observations that cannot be diagnosed convincingly
Strongly coupled components that implicate each other, so they cannot be effectively separated in diagnosis
Components whose failures are misinterpreted as failures of other components

10. Sample Graph for Car Diagnosis Bayesian Network Model[1]
Fuel Level
Fuel Filter
Battery
Fuel Pump
Starter
Induction Coil
Cable

11. 2-D Matrix for Car Diagnosis Bayesian Network Model1]
Starter
Fuel Level
Battery
Cable
Fuel Pump
Fuel Filter
Induction Coil I M P L C A T E D F U
True Defect
Prior
Probabilities

12. 3-D Matrix for Car Diagnosis Bayesian Network Model 1]
Prior
Probabilities I M P L C A T E D F U
Starter
Fuel Level
Battery
Cable
Fuel Pump
Starter
Fuel Level
Fuel Filter
Battery
Cable
Induction Coil
Fuel Pump
Fuel Filter
Induction Coil
True Defect

13. 3-D Matrix for Bayesian Network Model for the Large Network [1]

14. Results and Conclusions [1]
METHOD AND ALGORITHMS FOR ANALYSIS OF BAYESIAN NETWORKS FOR DIAGNOSTICS
SOFTWARE PACKAGE FOR COMPUTATION AND DISPLAY OF THE ANALYSIS RESULTS
CONCLUSIONS
THE RESULTS CAN BE USED AS A GUIDE IN TESTING OF THE MODEL
THE METHOD CAN BE USED IN DESIGN OF SYSTEMS FOR DIAGNOSIBILITY
THE METHOD IS APPLICABLE NOT ONLY TO DIAGNOSTICS
BUT TO GENERAL CLASS OF DECISION SUPPORT PROBLEMS