Subject Name: Pattern Recognition
and Computer Vision
Subject Code: ML-411T Semester:
7th
Assignment No. 2
Bloom’s
Taxonomy Levels: 1. Remember 2. Understand
3. Apply 4. Analyze 5. Evaluate 6. Create
|
Q.
No. |
Question |
BTL
level |
CO |
|
1. |
What
do you mean by fuzzy decision making? Also discuss the fuzzy classification
using suitable examples. |
1 |
2 |
|
2. |
What
do you understand by supervised learning and unsupervised learning? Explain.
Discuss any unsupervised learning algorithm with some examples. |
2 |
1 |
|
3. |
Briefly
explain segmentation and grouping. |
1 |
2 |
|
4. |
Explain
Gaussian Mixture Models. If for any two elements A<B given that P(A)=1/3,
P(B)=1/5 and P(AUB)=11/30, then find:
P(A/B). |
1 |
1 |
|
5 |
Explain
chi-square test. |
1 |
1 |
|
6. |
Explain
evaluation of classifiers. Give probability distribution of a random
variable. |
3 |
2 |
|
7. |
Explain
why the maximum likelihood estimation is not working with uniformly
distributed training sets. |
2 |
2 |
|
8. |
Show
that in the likelihood the sample mean is equal to the mean of samples. |
1 |
1 |
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