Indian Institute of Technology Madras
BS Degree Programme · Examination & Study Paper
Machine Learning Techniques
k-NN & decision trees
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.
End Term · 31 Aug 2025 (FN)End Term
- Q1MSQ3 Marks·Choose all correct options
Which among the following is TRUE for k-NN algorithm? Select all that apply.
- A1-nearest neighbour is sensitive to outliers.
- Bk-NN can only be applied to a classification problem.
- CAs k increases, the model is more likely to overfit.
- DThe bias increases with the increase in the value of k.
- EThe variance increases with the increase in the value of k.
End Term · 31 Aug 2025 (AN)End Term
- Q2MSQ3 Marks·Choose all correct options
Which of the following statements are true about the decision tree algorithm?
- ADecision trees are prone to overfitting if the maximum depth is set too shallow.
- BDecision trees are not affected by the order of features in the dataset.
- CDecision trees are sensitive to small perturbations in the dataset and can result in different tree structures.
- DDecision trees can handle both numerical and categorical features.
Quiz 2 · 3 Aug 2025 (AN)Quiz 2
- Q3NAT3 Marks·Write the number
Your answer: Read the passage below, then answer Q4–Q5
Based on the above data, answer the given subquestions.
Q4MCQ3 Marks·Choose one optionWhich among the following represents the correct decision boundary for the decision tree? Note: Here + represents the label 1 and − represents the label 0.
- A
- B
- C
- D
- A
- Q5NAT2 Marks·Write the number
What will be the prediction for the new datapoint (2, 2)?
Your answer: Read the passage below, then answer Q6–Q7
Suppose you want to build a decision tree to help diagnose a certain disease based on patient data. You have a dataset of 1000 patients labeled as either “positive” or “negative”. Here, positive represents patients with the disease and negative represents no disease. One of the feature used to diagnose is headache.
Below is the breakdown of the patients reporting headache:
Headache present: 300 positive, 50 negative
Headache not present: 100 positive, 550 negative
Based on the above data, answer the given subquestions.
Q6NAT3 Marks·Write the numberWhat is the entropy of the root node? Enter the answer correct to two decimal places.
Your answer:- Q7NAT4 Marks·Write the number
What is the information gain for choosing the feature “headache” for splitting at the root node? Enter the answer correct to two decimal places.
Your answer:
End Term · 13 Apr 2025 (FN)End Term
- Q8MCQ3 Marks·Choose one option
For a given dataset, a 1-Nearest Neighbor (1-NN) and a 3-Nearest Neighbor (3-NN) classifier are applied. Which classifier is likely to exhibit a higher Leave-One-Out Cross Validation (LOOCV) error? In case of tie-breaker, assign a positive class (+) to the data point.
- A1-NN
- B3-NN
- CBoth have the same error.
- Q9NAT2 Marks·Write the number
For a decision tree, each node has exactly two child nodes (balanced tree). If the tree has a depth of 3, how many leaf nodes are there?
Your answer:
End Term · 13 Apr 2025 (AN)End Term
- Q10MSQ2 Marks·Choose all correct options
Which of the following conditions must be satisfied for a decision tree to be pure at a given node?
- AThe entropy of the node is maximum.
- BThe information gain at the node is negative.
- CAll samples at a node belong to the same class.
- DThe entropy of the node is 0.