NPTEL Introduction to Machine Learning IITKGP Week 1 Assignment Answers 2025

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NPTEL Introduction to Machine Learning IITKGP Week 1 Assignment Answers 2025

1. Which of the following are classification tasks?
   A. Find the gender of a person by analyzing his writing style
   B. Predict the price of a house based on floor area, number of rooms, etc.
   C. Predict the temperature for the next day
   D. Predict the number of copies of a book that will be sold this month
   Answer: A
   Classification tasks involve predicting categories or labels. Gender prediction is a classification problem.
2. Which of the following is not a categorical feature?
   A. Gender of a person
   B. Height of a person
   C. Types of mountains
   D. Nationality of a person
   Answer: B
   Height is a numerical feature. The others are categorical.
3. Which of the following tasks is NOT a suitable machine learning task?
   A. Finding the shortest path between a pair of nodes in a graph
   B. Predicting if a stock price will rise or fall
   C. Predicting the price of petroleum
   D. Grouping emails as spams or non-spams
   Answer: A
   Shortest path is solved with algorithms like Dijkstra’s, not ML.
4. Suppose you have 10,000 emails in your mailbox, out of which 200 are spams. The spam detection system detects 150 mails as spams, out of which 50 are actually spams. What is the precision and recall?
   A. Precision = 33.33%, Recall = 25%
   B. Precision = 25%, Recall = 33.33%
   C. Precision = 33.33%, Recall = 75%
   D. Precision = 75%, Recall = 33.33%
   Answer: A
   Precision = 50/150 = 33.33%, Recall = 50/200 = 25%
5. A feature F1 can take values: A, B, C, D, E, F (grades of students). Which statement is true?
   A. Nominal variable
   B. Ordinal variable
   C. None of the above
   D. Both of these
   Answer: B
   Grades have a natural ordering, so they’re ordinal variables.
6. Which learning paradigm is best for training a robotic arm in automotive industry?
   A. Supervised learning
   B. Unsupervised learning
   C. Combination of supervised and unsupervised learning
   D. Reinforcement learning
   Answer: D
   Reinforcement learning is used for tasks needing sequential decisions.
7. How many Boolean functions are possible with N features?
   A. 2^2N
   B. 2^N
   C. N²
   D. 4N
   Answer: A
   There are 2^2N Boolean functions with N inputs.
8. What is the use of Validation dataset in Machine Learning?
   A. To train the model
   B. To evaluate the performance
   C. To tune hyperparameters
   D. None of the above
   Answer: C
   Validation set is used for hyperparameter tuning.
9. Regarding bias and variance, which statements are true?
   A. Overfit models have high bias.
   B. Overfit models have low bias.
   C. Underfit models have high variance.
   D. Underfit models have low variance.
   Answer: B, D
   Overfitting = low bias, high variance. Underfitting = high bias, low variance.
10. Is the following statement true or false? “Occam’s Razor is an example of Inductive Bias”
    A. True
    B. False
    Answer: A
    Occam’s Razor favors simpler models—an inductive bias in ML.
11. Which of the following is a categorical feature?
    A. Height of a person
    B. Price of petroleum
    C. Mother tongue of a person
    D. Amount of rainfall
    Answer: C
    “Mother tongue” is a categorical feature.

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