A Machine Learning practitioner needs to estimate the parameters of a model, given some data . Suppose, that the parameters can take only two values, 1 or 2 and that it is given that (|1) = 0.6, (|2) = 0.5, (1) = 0.3, and (2) = 0.7.

i) What does each of the terms (|) and (), {1,2} denote?

ii) Which model will he/she choose under the Maximum Likelihood criterion? Which model will he/she choose under the Maximum Aposteriori Probability criterion? Show the calculations.