# NPTEL Introduction to Machine Learning Assignment 9 Answers 2022 Are you looking for the Answers to NPTEL Introduction to Machine Learning Assignment 9 – IIT Madras? This article will help you with the answer to the National Programme on Technology Enhanced Learning (NPTEL) Course “NPTEL Introduction to Machine Learning Assignment 9

## What is Introduction to Machine Learning?

With the increased availability of data from varied sources there has been increasing attention paid to the various data driven disciplines such as analytics and machine learning. In this course we intend to introduce some of the basic concepts of machine learning from a mathematically well motivated perspective. We will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms.

## CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of the average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF THE AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Below you can find the answers for NPTEL Introduction to Machine Learning Assignment 9

## NPTEL Introduction to Machine Learning Assignment 9 Answers:-

Q1. In the undirected graph given below, which nodes are conditionally independent of each other given a single other node (may be different for different pairs)? Select all that apply.

a. 3, 2
b. 0, 4
c. 2, 5
d. 1, 5

Q2. Given the following conditional probability table for

• x1 is independent of x2
• x2 is independent of x1
• Both are independent of each other
• Neither is independent of the other

For Online programming test help and final exam preparation material Click Me

Q3. Statement 1: Probability distributions are valid potential functions.

Statement 2: Probability is always strictly positive.

• Statement 1 is true. Statement 2 is true. Statement 2 is the correct reason for statement 1.
• Statement 1 is true. Statement 2 is true. Statement 2 is not the correct reason for statement 1.
• Statement 1 is true. Statement 2 is false.
• Both statements are false.

Q4. Given graph below:

Q5. Given the directed graph(DG) and undirected graphs(UG) below, what is the relation between their Markov Blankets(MB) of node A?

Q6. Given below is the DG from Q5 with reversed edges. What is the relation between its MB with the UG in Q5?

Q7. Which of these can be modeled as a HMM (select all that apply)?

Q8. Four random variables are known to follow the given factorization

Q9. Given graph below:

Representing the properties in the graph using their initial letter, which of the given options are valid factorizations to calculate P(L=l)P(L=l) according to variable elimination (need not be the optimal order)?
Select all that apply.

Q10. Which of the following methods are used for calculating conditional probabilities? (more than one may apply)