1. Consider the following sample data set for Car Theft. Using a Nave Bayes Classifier train the above data set. a) For the following data, Classify/Predict whether the car would be stolen or not? 1. Red SUV Domestic 2. Black SUV Imported 3. Yellow Imported 4. Black Sports Note: you do not need to include each test data in the training data set after you predict the class. b) After you predict the 2nd test data, include the observations in the training data set and now predict the 3rid and 4th test data. Did the results change? Neatly show all the steps/calculations. 2. You will model a small Bayesian network that represents the relationship between yellow fingers, smoking, cancer, radiation, solar flares, and using a microwave. In this model, smoking can cause yellow fingers and cancer. Solar flares and making microwave popcorn can cause radiation, and radiation can cause cancer as well. The prior probability of smoking P(S) is 0.3. The prior probability of solar flares P(F) is 0.8. The prior probability of using the microwave is P(M) is 0.9