STUPIDSID
Solve any one question from Q.1(a,b) & Q.2(a,b)
1(a)
Explain logical models. State examples.
5 M
1(b)
What is a perceptron? Explain with the help of an example.
5 M
2(a)
With an example, explain feature as a split and feature as a predictor.
5 M
2(b)
Calculate accuracy, precision and recall for the following:
| Predicted + | Predicted - | |
| Actual + | 60 | 15 |
| Actual - | 10 | 15 |
5 M
Solve any one question from Q.3(a,b) & Q.4(a,b)
3(a)
When is it suitable to use linear regression over classification?
5 M
3(b)
State formulate for calculating accuracy, true positive rate, true negative rate, false positive rate and false negative rate for binary classification tasks.
5 M
4(a)
Explain training dataset, test dataset and supervised learning.
5 M
4(b)
Why do we need to regularize in regression? Explain.
5 M
Solve any one question from Q.5(a,b) & Q.6(a,b)
5(a)
Explain four distance function. Name any machine learning task which uses distance functions.
9 M
5(b)
Write note on clustering trees.
9 M
6(a)
Write a note on subgroup discovery.
9 M
6(b)
Explain single linkage, complete linkage and average linkage.
9 M
Solve any one question from Q.7(a,b) & Q.8(a,b)
7(a)
Is Naive Bayes algorithm supervised or unsupervised task? Explain how it achieves the task you specified.
8 M
7(b)
Write a note on normal distribution.
8 M
8(a)
What is multivariate Bernoulli distribution?
8 M
8(b)
Using the following data, find 2-item-itemsets which have minimum support =2.
| Transaction | Items |
| 1 | nappies |
| 2 | beer, crisps |
| 3 | apples, nappies |
| 4 | beer, crisps, nappies |
| 5 | apples |
| 6 | apples, beer, crisps, nappies |
| 7 | apples, crisps |
| 8 | crisps |
8 M
Solve any one question from Q.9(a,b) & Q.10(a,b)
9(a)
Write a note on reinforcement learning.
8 M
9(b)
Write a note on On-line learning.
8 M
10(a)
Write a note on Deep Learning.
8 M
10(b)
Write a note on ensemble learning.
8 M
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