Which of the following estimators are more likely to be preferred for bagging? Select all that apply.
A decision stump
A fully grown decision tree with randomly selected features for splitting the nodes.
k-NN classifier with a smaller value of k.
k-NN classifier with a larger value of k.
What will be the result of applying ReLU to the following values?:
-3.7, 4.9, -2.0, 5.2, 7.4, -8.3
1, 4.9, 1, 5.2, 7.4, 1
0, 1, 0, 1, 1, 0
0, 4.9, 0, 5.2, 7.4, 0
-1, +1, -1, +1, +1, -1
-3.7, 0, -2.0, 0, 0, -8.3
Suppose you run gradient descent for linear regression for 100 iterations with a learning rate 0.01. You observe that the training loss (sum of squared loss) is increasing after every iteration. What may be the reason? What changes would you make to the set-up for the gradient descent to converge to a solution?
Learning rate may be too low; Try increasing it.
Learning rate may be too high; Try reducing it.
Number of features in the training data may be too low, try increasing them.
Number of features in the training data may be too high, try reducing them.
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The IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 11 Dec 2022, in the September 2022 term, set ETD1-2: 30 questions for 100 marks in 180 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.
| Feature | MLT End Term 11 Dec 2022 Set ETD1-2 at a glance |
|---|---|
| Term | September 2022 term |
| Subject | Machine Learning Techniques |
| Course code | BSCS2007 |
| Questions | 30 |
| Marks | 100 |
| Duration | 180 min |
| MSQ | 3 |
| MCQ | 12 |
| Numerical | 15 |
| Official paper | IIT M DIPLOMA AN1 EXAM ETD1 11 Dec 2022 |
| Negative marking | No negative marking. |
| Updated |
