During classification of linearly separable data-set using perceptron algorithm, as the value of learning rate α is decreased,
The number of steps required for convergence increases.
The number of steps required for convergence decreases.
The number of steps required for convergence is independent of the learning rate.
The perceptron algorithm may not converge.
A knn algorithm with k = 30 gives high training error and high validation error. What value of the k we should choose to get the better performance of the
algorithm?
Less than 30
Greater than 30
Consider a binary classification problem. Let p1 denote the proportion of class 0 examples in a particular node. Which of the following graphs shows correct curves for the Gini-index, Entropy and misclassification error of that node?
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The IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 7 Aug 2022, in the May 2022 term, set QPD1: 33 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 7 Aug 2022 Set QPD1 at a glance |
|---|---|
| Term | May 2022 term |
| Subject | Machine Learning Techniques |
| Course code | BSCS2007 |
| Questions | 33 |
| Marks | 100 |
| Duration | 180 min |
| MCQ | 10 |
| MSQ | 6 |
| Numerical | 17 |
| Official paper | IIT M FOUNDATION DIPLOMA ENDTERM QPD1 07 Aug 2022 IBA NS |
| Negative marking | No negative marking. |
| Updated |
