BCS602 – Machine Learning Solved Model Question Paper with Solutions
Module 1
1.a] Define Machine Learning. Explain its relationship to other fields with a diagram.
1.b] Explain different types of Machine Learning with a diagram.
OR
2.a] Define data. Explain the 6 V’s of Big Data.
2.b] Explain data preprocessing with an example.
Module 2
3.b] Explain continuous and discrete probability distributions.
OR
4.a] Design a learning system for a chess game.
4.b] Explain and apply Candidate Elimination Algorithm for the given dataset.
Module 3
OR
6.b] Analyze decision tree learning with its structure, advantages, and disadvantages.
Module 4
7.a] Define Prior Probability. Explain Bayes Theorem, hML and hMAP with an example.
OR
8.a] Analyze different types of Artificial Neural Networks with a diagram.
8.b] Define Activation Function. Explain different types of activation functions.
Module 5
9.a] Analyze Grid-based approach and mention the steps of CLIQUE.
9.b] Apply K-Means Clustering Algorithm for the given data with initial seeds as objects 2 and 5:
| Object | X-Coordinate | Y-Coordinate |
|---|---|---|
| 1 | 2 | 4 |
| 2 | 4 | 6 |
| 3 | 6 | 8 |
| 4 | 10 | 4 |
| 5 | 12 | 4 |
OR
10.a] Determine characteristics, applications, and challenges of Reinforcement Learning.
10.b] Analyze components of Reinforcement Learning with a diagram.