Assignment5

=**CSE655: Probabilistic Reasoning**=

Problem 1

 * Using the BN model you developed as part of Assignment # 3 (Part 2), generate a data set of 2000 records and learn the structure of a BN using BN Power Constructor. How much the learned model matches with the actual model (You can define your own criterion to match similarity between two models).
 * Repeat the exercise after generating data sets of 5000 and 10,000. Does increasing the sample size has any impact on the similarity level?

Problem 2

 * Test the sensitivity of node “H” on the root nodes {“A”, “B”, “C”, “D”} in the following Bayesian Network. [[file:HW Last.xdsl]]
 * Use the following two techniques:
 * Entropy based calculations (Unit # 14, Slide # 3)
 * Sensitivity Analysis as done in Influence Nets (Unit # 14, Slide # 6)
 * Sort the root nodes in terms of their influences on node “H”.

Problem 3

 * Consider the above Timed Influence Net. [[image:TIN.jpg]]
 * Suppose action “A” is taken at time 4 and “B” at time 3. Draw the probability profile of node D. To simplify the calculations, CPTs are provided instead of the CAST logic parameters.
 * Using the transformation technique discussed in “From Dynamic Influence Nets to Dynamic Bayesian Networks: A Transformation Algorithm” paper, transform this Timed Influence Net into an equivalent Dynamic Bayesian Network.