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IIT M DIPLOMA AN3 EXAM QDD3 03 Dec 2023 - 03 Dec 2023

MLP Quiz 223 questions50 marks13 MCQ · 8 MSQ · 2 SADiploma / QDD3
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Q1MCQ1 mark
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  1. 1
  2. 2
  3. 10
  4. 500
Q2MCQ1 mark
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  1. (4, 3)
  2. (3, 4)
  3. (4, 4)
  4. (3, 3)
Q3MCQ2 marks
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Q4MCQ2 marks
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Q5MCQ2 marks
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Q6MCQ2 marks
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  1. It will perform regression on the given data.
  2. It will generate synthetic regression data.
  3. It will perform classification on the given data.
  4. It will generate synthetic classification data.
Q7MCQ2 marks
Which method of classification needs more than n classifiers, where n is the number of classes?
  1. OneVsRestClassifier
  2. OneVsOneClassifier
  3. OutputCodeClassifier
  4. MultiOutputClassifier
Q8MCQ2 marks
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  1. alpha
  2. tol
  3. solver
  4. learner
  5. algo
  6. algorithm
Q9MCQ2 marks
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  1. 0
  2. 1
  3. 2
  4. Can not be determined without knowing the test data point.
Q10MCQ2 marks
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Q11MCQ3 marks
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  1. It applies the perceptron classification with regularization.
  2. It applies the perceptron classification without regularization.
  3. It applies the logistic regression with regularization.
  4. It applies the logistic regression without regularization.
Q12MCQ3 marks
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  1. A total of 12 estimators will be trained, with each estimator using 3-foldcrossvalidation
  2. The parameter combination will be the same in every run becauserandom_state is set to 0.
  3. Given code will throw an error because all the parameters are not presentedas a list
  4. All of the options are incorrect
Q13MCQ4 marks
According to DecisionTreeClassifier parameters which of the following option will have least fitting(underfit) for the same data.
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Q14MSQ2 marksselect all that apply
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Q15MSQ2 marksselect all that apply
Which of the following is/are true about DummyClassifier?
  1. DummyClassifier makes predictions that ignore the input features.
  2. DummyClassifier serves as a simple baseline to compare against other morecomplex classifiers.
  3. The predictions of DummyClassifier typically depend on values observed in they parameter passed to fit().
  4. The predictions of DummyClassifier typically depend on values observed in theX parameter passed to fit().
  5. All of these.
Q16MSQ2 marksselect all that apply
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Q17MSQ2 marksselect all that apply
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Q18MSQ2 marksselect all that apply
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Q19MSQ2 marksselect all that apply
Which of the following are advantages of using ensemble methods in machine learning?
  1. Improved model performance
  2. Reduced overfitting
  3. Faster model training
  4. Simplicity of model interpretation
Q20MSQ3 marksselect all that apply
Which of the following option(s) are True ?
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Q21MSQ3 marksselect all that apply
Suppose In a classification problem you want to use BaggingClassifier, which of the following estimator(s) could be used as base estimator in that?
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Q22SA2 marks
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Answer key

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