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2024 Aug04: IIT M AN EXAM QDD3 - 04 Aug 2024

MLT Quiz 223 questions40 marks19 SA · 2 MSQ · 2 MCQafternoon / QDD3
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Q1MSQ3 marksselect all that apply
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Q2SA3 marks
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Q3SA3 marks
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Q4SA3 marks
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Comprehension passage - the questions below it refer to this
Based on the above data, answer the given subquestions. question figure
Q5SA2 marks
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Q6SA2 marks
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Comprehension passage - the questions below it refer to this
Based on the above data, answer the given subquestions. question figure
Q7SA1.5 marks
How many models have to be trained?
Q8SA1.5 marks
While training each of these models, how many data-points does the training set have?
Comprehension passage - the questions below it refer to this
Based on the above data, answer the given subquestions. question figure
Q9MCQ1 mark
What kind of a regression problem is this?
  1. Ridge regression
  2. LASSO regression
Q10SA0.5 marks
What is the optimal value of w1?
Q11SA0.5 marks
What is the optimal value of w2?
Q12MCQ1 mark
Which of the following statements is true?
  1. Feature-1 can be discarded.
  2. Feature-2 can be discarded.
  3. Any one of the two features can be discarded.
  4. Both features are equally important and neither of them can be discarded.
Q13MSQ2 marksselect all that apply
Which of the following statements are true? Exactly two options are correct.
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Comprehension passage - the questions below it refer to this
If a and b are integers, answer the given subquestions that follow. Hint: Plotting the dataset helps. question figure
Q14SA1 mark
What is the value of a?
Q15SA1 mark
What is the value of b?
Q16SA1 mark
Find the entropy of the root node. Use log2______________________.
Q17SA2 marks
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Q18SA1 mark
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Comprehension passage - the questions below it refer to this
Assume that there is no smoothing. Answer the given subquestions. question figure
Q19SA2 marks
Find the value of c + d.
Q20SA2 marks
Find the value of a + c + e.
Q21SA2 marks
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Comprehension passage - the questions below it refer to this
Consider a multi-class classification problem with 3 classes and 4 features, all of which are binary. A generative model is used to model the joint distribution of the features and labels. Based on the above data, answer the given subquestions.
Q22SA2 marks
Find the total number of independent (free) parameters in the model if the class conditional independence assumption is not enforced.
Q23SA2 marks
Find the total number of independent (free) parameters in the model if the class conditional independence assumption is enforced.

Answer key

  1. Q1 (MSQ, 3 marks): A, B
  2. Q2 (SA, 3 marks): 0.73
  3. Q3 (SA, 3 marks): 0.625
  4. Q4 (SA, 3 marks): 6
  5. Q5 (SA, 2 marks): 2
  6. Q6 (SA, 2 marks): 0.1
  7. Q7 (SA, 1.5 marks): 4
  8. Q8 (SA, 1.5 marks): 750
  9. Q9 (MCQ, 1 marks): B
  10. Q10 (SA, 0.5 marks): 1
  11. Q11 (SA, 0.5 marks): 0
  12. Q12 (MCQ, 1 marks): B
  13. Q13 (MSQ, 2 marks): A, C
  14. Q14 (SA, 1 marks): 0
  15. Q15 (SA, 1 marks): 0
  16. Q16 (SA, 1 marks): 1
  17. Q17 (SA, 2 marks): 1
  18. Q18 (SA, 1 marks): 1
  19. Q19 (SA, 2 marks): 1.25
  20. Q20 (SA, 2 marks): 1.5
  21. Q21 (SA, 2 marks): 0
  22. Q22 (SA, 2 marks): 47
  23. Q23 (SA, 2 marks): 14