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MLT · End Term · 31 Aug 2025 (Afternoon)

17 questions · 50 marks · 90 min

Answer key Take as mock

Indian Institute of Technology Madras

BS Degree Programme · Examination & Study Paper

Machine Learning Techniques

End Term · 31 Aug 2025 (Afternoon)

Official Paper

Examination Instructions & Guidelines

Solve on notebook/paper first before checking solutions.
MCQ: Exactly 1 option is correct. Negative marking applies.
MSQ: One or more options correct. Select all to score.
NAT: Numerical response. No negative marking.
Scientific calculator allowed for all calculations.
Official answer key is sealed at the end of this sheet.

Q1MCQ3 Marks·Choose one option
Asked 3 times Key ↓
1. AYes
2. BNo
Q2MCQ3 Marks·Choose one option
Asked 2 times Key ↓
1. A
2. B
3. C
4. D
Q3MCQ2 Marks·Choose one option
Asked 2 times Key ↓
1. A
2. B
3. C
4. D
Q4MCQ2 Marks·Choose one option
Key ↓
1. AGreedy initialization always achieves F = F_(optimal) by maximizing the distance between initial centers.
2. BGreedy initialization may achieve F = F_(optimal) or a larger value depending on the dataset and the initial choice.
3. CGreedy initialization does not ensure convergence for K-means clustering.
4. DGreedy initialization ensures convergence to a unique solution for any dataset.
Q5MCQ4 Marks·Choose one option
Asked 4 times Key ↓
1. A
2. B
3. C
4. D
Q6MSQ3 Marks·Choose all correct options
Key ↓
Which of the following statements are true about the decision tree algorithm?
1. ADecision trees are prone to overfitting if the maximum depth is set too shallow.
2. BDecision trees are not affected by the order of features in the dataset.
3. CDecision trees are sensitive to small perturbations in the dataset and can result in different tree structures.
4. DDecision trees can handle both numerical and categorical features.
Q7MSQ3 Marks·Choose all correct options
Asked 2 times Key ↓
1. A
2. B
3. C
4. D
Q8MSQ3 Marks·Choose all correct options
Key ↓
1. A
2. B
3. C
Q9MSQ4 Marks·Choose all correct options
Key ↓
Given a two-dimensional data set where points from class 1 are: {(−2, 3), (−1, 1)} and points from class 0 are: {(1, 3), (1, 4)}. Which of the following statements are true?
1. AThe given data points from classes 1 and 0 can be linearly separated using a hard-margin SVM.
2. BA perceptron model and a hard-margin SVM can give different decision boundary for this dataset.
3. CA soft-margin SVM would be a more robust choice than a hard-margin SVM for this dataset as the dataset is not linearly separable.
4. DThe width of the separation between the two supporting hyperplanes is 4.
Q10NAT3 Marks·Write the number
Key ↓
Your answer:
Q11NAT3 Marks·Write the number
Asked 2 times Key ↓
Your answer:
Q12NAT3 Marks·Write the number
Key ↓
Your answer:
Q13NAT4 Marks·Write the number
Asked 3 times Key ↓
Your answer:
Read the passage below, then answer Q14–Q15
Based on the above data, answer the given subquestions.
Q14MCQ4 Marks·Choose one option
Asked 2 times Key ↓
1. A
2. B
3. C
4. D
Q15MCQ2 Marks·Choose one option
Asked 2 times Key ↓
1. AThe coefficients shrinks towards zero.
2. BThe coefficients increases in magnitude.
3. CThe coefficients remain unchanged.
Read the passage below, then answer Q16–Q17
Based on the above data, answer the given subquestions.
Q16NAT1 Mark·Write the number
Asked 2 times Key ↓
Your answer:
Q17NAT3 Marks·Write the number
Asked 2 times Key ↓
Your answer:

Official Key

Master Answer Key & Explanations

Official answer keys from IIT Madras BS past papers. Click any question to review.

Reveal Key

Q1B

Q2C

Q3B

Q4B

Q5D

Q6C, D

Q7A, D

Q8A, B

Q9A, B

Q106

Q111.1 to 1.14

Q121

Q130.28 to 0.34

Q14C

Q15B

Q167

Q170.0625

Questions and answer keys are reproduced from the official IIT Madras BS papers. BTechi is not affiliated with IIT Madras.