# Question: Consider an arbitrary Bayesian network a complete data set for

Consider an arbitrary Bayesian network, a complete data set for that network, and the likelihood for the data set according to the network. Give a simple proof that the likelihood of the data cannot decrease if we add a new link to the network and re-compute the maximum likelihood parameter values.

**View Solution:**## Answer to relevant Questions

Consider the application of EM to learn the parameters for the network in Figure (a), given the true parameters in Equation (20.7).a. Explain why the EM algorithm would not work if there were just two attributes in the model ...Consider the following set of examples, each with six inputs and one target output:a. Run the perception learning rule on these data and show the final weights.b. Run the decision tree learning rule, and show the resulting ...Defined a proper policy for an MDP as one that is guaranteed to reach a terminal state, show that it is possible for a passive ADP agent to learn a transition model for which its policy π is improper even if π is ...Extend the standard game-playing environment to incorporate a reward signal. Put two reinforcement learning agents into the environment (they may, of course, share the agent program) and have them play against each other. ...This exercise concerns grammars for very simple languages.a. Write a context-free grammar for the language anbn.b. Write a context-free grammar for the palindrome language: the set of all strings whose second half is the ...Post your question