2. Road Map
PART-II: July 24, 2017 (based on PART-I)
1. Estimating Mutual Information (15 mins)
2. Learning Forests from Data (25 mins)
3. Learning Bayesian Networks from Data (5 mins)
4. Exercise (45 mins)
PART-I: July 17, 2017
A Bayesian Approach to Data Compression
22. Experiments using Asia data set
• library(BNSL)
• mm=mi_matrix(asia, proc=9) # I_n is used
• edge.list=kruskal(mm)
• g=graph_from_edgelist(edge.list, directed=FALSE)
• plot(g)
• mm=mi_matrix(asia) # J_n is used
• edge.list=kruskal(mm)
• g=graph_from_edgelist(edge.list, directed=FALSE)
• plot(g)
23. Asia (8 variables)
S. Lauritzen, D. Spiegelhalter. Local
Computation with Probabilities on
Graphical Structures and their
Application to Expert Systems (with
discussion). Journal of the Royal
Statistical Society: Series B
(Statistical Methodology), 50(2):157-
224, 1988
25. I. A. Beinlich, H. J. Suermondt, R. M.
Chavez, and G. F. Cooper. The ALARM
Monitoring System: A Case Study
with Two Probabilistic Inference
Techniques for Belief Networks. In
Proceedings of the 2nd European
Conference on Artificial Intelligence
in Medicine, pages 247-256.
Springer-Verlag, 1989.
Alarm (37 varibles)