# AML Quiz 2 Section B

10 Questions | Total Attempts: 75  Settings  QUIZ 2 SECTION B

• 1.
Consider the following Bayesian network, where F stands for Flu and C stands for Coughing. Find P(C).
• A.

0.35

• B.

0.77

• C.

0.24

• D.

0.5

• 2.
Which of the following graphical models capture the Naive Bayes assumption, where c represents the class label and fi are the features.
• A.

Option 1

• B.

Option 2

• C.

It cannot be captured by a graphical model

• 3.
Suppose you are given 7 Scatter plots 1-7 (left to right) and you want to compare Pearson correlation coefficients between variables of each scatterplot. Which of the following is in the right order?   1. 1<2<3<4   2. 1>2>3 > 4   3. 7<6<5<4   4. 7>6>5>4
• A.

1 and 3

• B.

2 and 3

• C.

1 and 4

• D.

2 and 4

• 4.
Bayesian Network is a graphical model that efficiently encodes the joint probability distribution for a large set of variables .
• A.

True

• B.

False

• 5.
A fair coin is tossed three times and a T (for tails) or H (for heads) is recorded, giving us a list of length 3. Let X be the random variable which is zero if no T has another T adjacent to it, and is one othetwise. Let Y denote the random variable that counts the number of T's in the three tosses. Find P(X=1, Y=2).
• A.

1/8

• B.

2/8

• C.

7/8

• D.

5/8

• 6.
To safeguard your house, you recently installed two different burglary alarm systems by two different reputable manufacturers that use completely different sensors for their alarm systems. Alarm1 means that the first alarm system rings, Alarm2 means that the second alarm system rings, and Burglary means that a burglary is in progress. Which one of the two Bayesian networks given below makes independence assumptions that are not true?
• A.

1

• B.

2

• C.

Both

• D.

None of these

• 7.
Consider the following graphical model. Mark which of the following pair of random variables is independent giveh no evidence?
• A.

A, b

• B.

C,d

• C.

E,d

• D.

C,e

• 8.
In the following Bayesian network A, B and C are Boolean random variables taking values in {True, False}. Which of the following statements is true?
• A.

The value of C is not given.If the value of B changes from True to False, the conditional probability of A, P(A/B) changes.

• B.

The value of C is given to be True. If the value of B changes from True to False the conditional probability of A, P(AIB) changes.

• C.

Neither A nor B

• D.

Both A and B

• 9.
Which of the following necessitates feature reduction in machine learning?
• A.

Irrelevant and redundant features.

• B.

Limited training data.

• C.

Limited computational resources.

• D.

All of the above.

• 10.
For which of the following cases Dimensional reduction may be used?
• A.

Data Compression

• B.

Data Visualization

• C.

To prevent over fitting

• D.

Both A and B Back to top