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Seat No.: Enrolment
GUJARAT TECHNOLOGICAL UNIVERSITY
MCA Integrated SEMESTER- VII- EXAMINATION WINTER 2018
Subject Code: 4470601 Date: 16-11-2018
Subject Name: Machine Learning
Time: 10.30 am to 1.00 pm Total Marks: 70
Instructions:
1. Attempt all questions.
2. Make suitable assumptions wherever necessary.
3. Figures to the right indicate full marks.
Q.1

Write a short note on-
Advantages of machine learning algorithms
Bayesian Belief Network
07

Write a short note on-
Concept learning
Artificial Neural Network(ANN)
07
Q.2

Design a learning system step by step for checker problem.
07

For the given data set find out the hypothesis using Candidate Elimination algorithm.
Sky
Temp
Humidity
Wind
Water
Forecast
Enjoy Sport
Sunny
Warm
Normal
Strong
Warm
Same
Yes
Sunny
Warm
High
Strong
Warm
Same
Yes
Rainy
Cold
High
Strong
Warm
Change
No
Sunny
Warm
High
Strong
Cool
Change
Yes
07
OR

Explain ID3 decision tree algorithm with suitable example.
07
Q.3

What is feed forward network? Discuss Backpropogation algorithm in detail.
07

Write formula for Bayes theorem. Explain Bayes theorem with suitable example.
07
OR
Q.3

Define perceptron. Write the formula for calculating errors at each output unit and updating the weights.
07

Explain Naïve Bayes classification algorithm.
07
Q.4

How Case based reasoning helps in learning? Explain with suitable example.
07

What is sample complexity for Probably Approximately Correct framework How it is different from mistake bound frame work?
07
OR
Q.4

Compare lazy and eager algorithm. Explain any one of lazy algorithm with example.
07

Explain Q learning with example.
07
Q.5

What do you understand by explanation based learning explain with PROLOG EGP algorithm.
07

Describe sequential covering algorithm.
07
OR
Q.5

Compare supervised, unsupervised and reinforcement algorithm with suitable example.
07

Discuss how First Order Horn clauses help in learning.
07