For this problem, you will use the house-votes-84.data data set provided with this problem set. Each row of the provided data file corresponds to a single observation of a voting record for a congressperson: the first entry is party affiliation and the remaining entries correspond to votes on different legislation with question marks denoting missing data.

(a). Using the first three features and the first 300 data observations only, fit a Bayesian network to this data using the EM algorithm for each of the eight possible complete DAGs over three variables.

(b). Do different runs of the EM algorithm produce different models?

(c). Evaluate your eight models, on the data that was not used for training, for the task of predicting party affiliation given the values of the other two features. Is the prediction highly dependent on the model that was fit?