Assume the following data has been collected from students:D I G S Lg0 sl 11g1 SO11go sl 1110g2 sli0 g3 s0 10dodod1d1d1d1dod1TELERARENili0ilili0 g2 s0 11i0 g3 s0 10ild1 ilg3 sl10g2 s0 10Describe the factors and find their parameters using ML training from the given data. (Hint: if you encounterdivision by zero you need to use Laplace smoothing: Assume the following Bayesian network that describes the chance of students getting into college based onrecommendation letters and SAT scores. Students' grades, the difficulty of the courses, and their intelligenceaffect their SAT scores and chances of getting good letters based on the given Bayesian network.DifficultyIntelligenceGradeLetterSATThe network has the following variables:• Difficulty: Val(D) = {d0, d1} = {easy, hard}• Intelligence: Val(I) = {i0, i1} = {non smart, smart}• Grade: Val(G) = {g0, g1, g2, g3} = {excellent, good, average, unsatisfactory}• SAT: Val(S) = {s0, s1} = {low score, high score}• Letter: Val(L) = {10,11} = {weak recomm. letter, strong recomm. letter}

In this Bayesian network scenario, the objective is to describe the factors and determine their…

Answered: Assume the following data has been…

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