AKTU MCA Machine Learning (KCA054) Question Paper 2021-22

Note: Attempt all Sections. If you require any missing data, then choose suitably.

Section A

Q1. Attempt all questions in brief · 2 × 10 = 20 marks

1. Define the term learning in Machine Learning.
2. List out the four issues in Machine Learning.
3. Describe logistic regression.
4. Explain the term Hyper Plane in SVM.
5. What is Instance Based Learning? 3
6. What is meant by information gain?
7. What is Perceptron in Artificial Neural Network?
8. Explain the function of Pooling Layer in CNN.
9. Identify four applications of reinforcement learning.
10. Define the term Mutation in Genetic Algorithm.

Section B

Q2. Attempt any three of the following · 10 × 3 = 30 marks

1. Explain the history of Machine Learning based on their application.
2. Explain Naïve bayes classifier and its principle.
3. List out the five Issues in Decision tree learning.
4. Differentiate between supervised and unsupervised learning.
5. Explain Markov decision process.

Section C

Q3

Attempt any one part of the following · 10 × 1 = 10 marks

1. How is clustering approach different from decision tree learning?
2. Describe the architecture of artificial neural network. State the learning parameters used in ANN.

Q4

Attempt any one part of the following · 10 × 1 = 10 marks

1. Explain in detail about Regression and its types.
2. What is the importance of support vector kernel? Explain its types.

Q5

Attempt any one part of the following · 10 × 1 = 10 marks

1. Describe ID-3 algorithm with an example.
2. Explain k-Nearest Neighbor Learning algorithm with an example.

Q6

Attempt any one part of the following · 10 × 1 = 10 marks

1. What is gradient descent problem? Explain its types.
2. Describe CNN architecture. Specify the function of each layer.

Q7

Attempt any one part of the following · 10 × 1 = 10 marks

1. Explain in detail about Q-learning and Deep Q-learning.
2. Explain Genetic Algorithm cycle of reproduction with its components.

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