Quiz Space

Machine Learning Techniques · End Term · 13 Apr 2025 · January 2025 term · Set QDD1

MLT End Term 13 Apr 2025 — Question 8

Question 8

+2 marksOne or more correct options

Select all that apply.

  1. A

    It penalizes large coefficients to reduce overfitting.

  2. B

    It shrinks the coefficients but does not set them to zero.

  3. C

    It forces more coefficients to be exactly zero, performing feature selection.

  4. D

    It has no effect on the regression model.

Show answer

Correct answers

  • A

    It penalizes large coefficients to reduce overfitting.

  • C

    It forces more coefficients to be exactly zero, performing feature selection.

Question 8 of 18 in the IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 13 Apr 2025, in the January 2025 term (IIT M DIPLOMA AN EXAM QDD3 13 Apr 2025). It carries 2 marks.

More questions from this paper

  1. Q1For a given dataset, a 1-Nearest Neighbor (1-NN) and a 3-Nearest Neighbor (3-NN) classifier are applied. Which classifi…
  2. Q2Consider the following three weight vectors obtained by minimizing the ridge regression objective with penalty paramete…
  3. Q3Consider the following dataset with two features and the corresponding labels: | x_1 | x_2 | y | |---|---|---| | 1 | 0 …
  4. Q4Consider a dataset with 4 datapoints: {(\mathbf{x}_1, y_1), (\mathbf{x}_2, y_2), (\mathbf{x}_3, y_3), (\mathbf{x}_4, y_…
  5. Q5Which of the following statements correctly differentiates PCA and Kernel PCA?
  6. Q6Consider the following formualtion of the soft margin SVM: \min_{w, \epsilon} \frac{1}{2} ||w||^2 + C \sum_{i=1}^{n} \e…
  7. Q7Which of the following statements are true for bagging?
  8. Q9For a decision tree, each node has exactly two child nodes (balanced tree). If the tree has a depth of 3, how many leaf…
  9. Q10Figure question
  10. Q11Let X_1, X_2, \ldots, X_n be i.i.d. samples from a Uniform distribution on the interval [0, \theta], where \theta is an…
  11. Q12Figure question
  12. Q13Find the squared length of the updated weight vector after one iteration (one pass through all the data points) of the …
  13. Q14Will the algorithm converge after this update?
  14. Q15Based on the above data, answer the given subquestions.
  15. Q16Which of the following training data points are certainly not support vectors?
  16. Q17Consider a single-layer neural network with two neurons in the hidden layer. The weight parameters of the network are g…
  17. Q18Consider a single-layer neural network with two neurons in the hidden layer. The weight parameters of the network are g…