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Machine Learning Question Paper - May 18 - Computer Engineering (Semester 8) - Mumbai University (MU)
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Machine Learning - May 18
Computer Engineering (Semester 8)
Total marks: 80
Total time: 3 Hours
INSTRUCTIONS
(1) Question 1 is compulsory.
(2) Attempt any three from the remaining questions.
(3) Draw neat diagrams wherever necessary.
Q1
a)
Define Machine learning? Briefly explain the types of learning.
(5 marks)
00
b)
What is independent component analysis.
(5 marks)
00
c)
What are the issues in decision tree induction?
(5 marks)
00
d)
What are the requirements of clustering algorithms?
(5 marks)
00
Q2
a)
The values of independent variable x and dependent value y are given below:
(10 marks)
00
| X | Y |
|---|---|
| 0 | 2 |
| 1 | 3 |
| 2 | 5 |
| 3 | 4 |
| 4 | 6 |
Find the least square regression line y=ax+b. Estimate the value of y when x is 10.
b)
What are the steps in designing a machine learning problem? Explain the checkers problem.
(10 marks)
00
Q3
a)
For a SunBurn dataset given below, construct a decision tree
(10 marks)
00
| Name | Hair | Height | Weight | Location | Class |
|---|---|---|---|---|---|
| Sunita | blonde | average | light | no | yes |
| anit | blonde | tall | average | yes | no |
| kavita | brown | short | average | yes | no |
| sushma | blonde | short | average | no | yes |
| xavier | red | average | heavy | no | yes |
| balaji | brown | tall | heavy | no | no |
| ramesh | brown | average | heavy | no | no |
| swetha | blonde | short | light | yes | no |
b)
What is the goal of the support vector machine (SVM)? How to compute the margin
(10 marks)
00
Q4
a)
For the given set of points identify clusters using complete link and average link using agglomerative clustering.
(10 marks)
00
| A | A | B |
|---|---|---|
| P1 | 1 | 1 |
| P2 | 1.5 | 1.5 |
| P3 | 5 | 5 |
| P4 | 3 | 4 |
| P5 | 4 | 4 |
| P6 | 3 | 3.5 |
b)
What is the role of radial basis function i separating nonlinear patterns.
(10 marks)
00
Q5
a)
Use Principle component analysis (PCA) to arrive at the transformed matrix for the given matrix A.
(10 marks)
00
$A^T$
$ \begin{bmatrix} 2 & 1 & 0 & -1 \\ 4 & 3 & 1 & 0.5 \end{bmatrix} $
b)
What are the elements of reinforcement learning?
(10 marks)
00
Q6 Write short notes on any two:
a)
Logistic regression
(10 marks)
00
b)
Back propogation algorithm
(10 marks)
00
c)
issues in machine Learning
(10 marks)
00
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