# NPTEL Introduction to Machine Learning Assignment 9 Answers

NPTEL Introduction to Machine Learning Assignment 9 Answers 2022:- In This article, we have provided the answers of Introduction to Machine Learning Assignment 9 You must submit your assignment to your own knowledge.

## 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.

## NPTEL Introduction to Machine Learning Assignment 9 Answers 2022:-

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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

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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

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?

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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.

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