Homework Help is Here – Start Your Trial Now!
Engineering
AI and Machine Learning
Assume the following data has been collected from students: D I G do il g0 s1 do i0 gl SO d1 il g0 sl d1 il g2 s1 d1 i0 g3 s0 i0 g2 s0 d1 do i0 g3 s0 S L 11 11 11 10 10 11 10 d1 il g3 sl 10 d1 il g2 s0 10 Describe the factors and find their parameters using ML training from the given data. (Hint: if you enc division bu zore you nood to uso Lonlege smoothing:

Assume the following data has been collected from students: D I G do il g0 s1 do i0 gl SO d1 il g0 sl d1 il g2 s1 d1 i0 g3 s0 i0 g2 s0 d1 do i0 g3 s0 S L 11 11 11 10 10 11 10 d1 il g3 sl 10 d1 il g2 s0 10 Describe the factors and find their parameters using ML training from the given data. (Hint: if you enc division bu zore you nood to uso Lonlege smoothing:

icon
Related questions
Question
Assume the following data has been collected from students: D I G S L g0 sl 11 g1 SO 11 go sl 11 10 g2 sl i0 g3 s0 10 do do d1 d1 d1 d1 do d1 TELERAREN il i0 il il i0 g2 s0 11 i0 g3 s0 10 il d1 il g3 sl 10 g2 s0 10 Describe the factors and find their parameters using ML training from the given data. (Hint: if you encounter division by zero you need to use Laplace smoothing:
Transcribed Image Text:Assume the following data has been collected from students: D I G S L g0 sl 11 g1 SO 11 go sl 11 10 g2 sl i0 g3 s0 10 do do d1 d1 d1 d1 do d1 TELERAREN il i0 il il i0 g2 s0 11 i0 g3 s0 10 il d1 il g3 sl 10 g2 s0 10 Describe the factors and find their parameters using ML training from the given data. (Hint: if you encounter division by zero you need to use Laplace smoothing:
Assume the following Bayesian network that describes the chance of students getting into college based on recommendation letters and SAT scores. Students' grades, the difficulty of the courses, and their intelligence affect their SAT scores and chances of getting good letters based on the given Bayesian network. Difficulty Intelligence Grade Letter SAT The 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}
Transcribed Image Text:Assume the following Bayesian network that describes the chance of students getting into college based on recommendation letters and SAT scores. Students' grades, the difficulty of the courses, and their intelligence affect their SAT scores and chances of getting good letters based on the given Bayesian network. Difficulty Intelligence Grade Letter SAT The 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}
Expert Solution
steps

Step by step

Solved in 3 steps with 1 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer