MEENAKSHI COLLEGE OF ENGINEERING
No.12.Vembuli Amman koil Street, West K.K. Nagar,
Chennai – 600 078
Department of Artificial intelligence and Data science
Model Examination
Programme & Batch: B.Tech AI&DS Year/Semester: II/IV
Subject Code/Title : AL3451 – Machine Learning Date :
Duration : 3Hrs Maximum : 100 marks
Instructions: Set :B
1. Before attempting any question paper, be sure that you got the correct question paper.
2. The missing data, if any, may be assumed suitably
3. Use the sketches wherever necessary
Course Outcomes
CO1: Explain the basic concepts of machine learning.
CO2: Construct supervised learning models.
CO3: Construct unsupervised leaming algorithms.
CO4: Evaluate and compare different models
CO5: Analyze machine learning experiments using cross-validation and statistical tests.
K
Leve
Qn.
Question Mark l (CO)
No
(K1-
K6)
Part A (10 * 2 = 20 Marks) Answer all Questions
What do you mean by hypothesis space?
1 2 K1 CO1
Write some examples for machine learning applications.
2 2 K1 CO1
Compare and contrast linear regression and logistic regression.
3 2 K1 CO2
Distinguish between Random Forest and Support Vector Machine.
4 2 K2 CO2
Define voting.
5 2 K1 CO3
Define Expectation Maximization.
6. 2 K2 CO3
7. List few activation functions. 2 K2 CO4
List the problems associated with Backpropagation Neural Network.
8. 2 K1 CO4
Give the use of Mc Neman’s test
9. 2 K2 CO5
10. How do you evaluate a Classification Algorithm 2 K1 CO5
Part B (5 * 13 = 65 Marks) Answer All Questions
Write detailed notes on Inductive Bias and Bias variance trade-off.
11a) 13 K1 CO1
OR
11b) Discuss the following 13 K2 CO1
(i) Vapnik - Chervonenkis (VC) Dimension.(7)
(ii) Probably Approximately Correct (PAC) Learning. (6)
Write an example and explain the Decision Tree concepts in detail.
12a) 13 K2 CO2
OR
By the method of least squares find the straight line to the data given
below.
x 5 10 15 20 25 CO2
12b) 13 K5
y 16 19 23 26 30
Cluster the following eight points with (x, y) representing locations) into
CO3
three clusters using K-means clustering method. A1(2, 10), A2(2, 5), A3(8,
13a) 13 K5
4), A4(5, 8), A5(7, 5), A6(6, 4), A7(1, 2), A8(4, 9).
OR
Compare Bagging, Boosting and Stacking ensemble methods.
13b) 13 K2 CO3
Illustrate the following
14a) (i) Batch Normalization. (7) 13 K1 CO4
(ii) Dropout.(6)
OR
Describe in brief about Multilayer perceptron activation functions.
14b) 13 K1 CO4
Elaborate the t test, McNemar's test and K-fold CV paired t test by giving
15a) your own example. 13 K2 CO5
OR
With neat diagram Validation technique.explain about K- fold Cross
15b) 13 K1 CO5
Part C (1 * 15 = 15 Marks) Answer All Questions
16a) 15 K5 CO5
The grades of a class of 9 students on a midterm report (X) and on the
x 77 50 71 72 81 94 96 99 67
y 82 66 78 34 47 85 99 99 68
final examination (Y) area as follows:
(i) Estimate the linear regression line.
(ii) Estimate the final examination grade of a student who received a
grade of 85 on the midterm report.
OR
Consider the following list that contains name, age, gender and class of
sports. In the Gender field males are denoted by the numeric value 0 and
females by 1. Using the K-Nearest Neighbor (KNN) algorithm, find class of
sports for a girl whose name is Angelina, her k factor is 3, and her age is
Ajay 32 0 Football
Mark 40 0 Neither
Sara 16 1 Cricket
16b) Zaira 34 1 Cricket 15 K5 CO1
Sachin 55 0 Neither
Rahul 40 0 Cricket
Pooja 20 1 Neither
Smith 15 0 Cricket
Laxmi 55 1 Football
Michael 15 0 Football
Knowledge Level as per Bloom Taxonomy
K1- Remember; K2- Understand; K3- Apply; K4- Analyze; K5- Evaluate; K6- Create
Course Instructor Dept Exam cell I/c HoD
