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.

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.

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.

CSE655: Probabilistic ReasoningAssignment # 5Date: January 10, 2010## Due Date: January 15, 2010

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