Deck 1: Fuzzy Logic, Set Theory, and Bayesian Networks

Question 1

Fuzzy logic is a form of

A)two-valued logic
B)crisp set logic
C)many-valued logic
D)binary set logic

Answer 1

many-valued logic

Question 2

The truth values of traditional set theory is ____________ and that of fuzzy set is __________

A)either 0 or 1, between 0 & 1
B)between 0 & 1, either 0 or 1
C)between 0 & 1, between 0 & 1
D)either 0 or 1, either 0 or 1

Answer 2

either 0 or 1, between 0 & 1

Question 3

How many types of random variables are available?

A)1
B)2
C)3
D)4

Answer 3

3

Question 4

The values of the set membership is represented by

A)discrete set
B)degree of truth
C)probabilities
D)both b & c

Question 5

What is meant by probability density function?

A)probability distributions
B)continuous variable
C)discrete variable
D)probability distributions for continuous variables

Question 6

Which of the following is used for probability theory sentences?

A)conditional logic
B)logic
C)extension of propositional logic
D)none of the mentioned

Question 7

Fuzzy Set theory defines fuzzy operators. Choose the fuzzy operators from the following.

A)and
B)or
C)not
D)ex-or

Question 8

There are also other operators, more linguistic in nature, called __________ that can be applied to fuzzy set theory.

A)hedges
B)lingual variable
C)fuzz variable
D)none of the mentioned

Question 9

Where does the Bayes rule can be used?

A)solving queries
B)increasing complexity
C)decreasing complexity
D)answering probabilistic query

Question 10

What does the Bayesian network provides?

A)complete description of the domain
B)partial description of the domain
C)complete description of the problem
D)none of the mentioned

Question 11

Fuzzy logic is usually represented as

A)if-then-else rules
B)if-then rules
C)both a & b
D)none of the mentioned

Question 12

______________ is/are the way/s to represent uncertainty.

A)fuzzy logic
B)probability
C)entropy
D)all of the mentioned

Question 13

____________ are algorithms that learn from their more complex environments (hence eco) to generalize, approximate and simplify solution logic.

A)fuzzy relational db
B)ecorithms
C)fuzzy set
D)none of the mentioned

Question 14

Which condition is used to influence a variable directly by all the others?

A)partially connected
B)fully connected
C)local connected
D)none of the mentioned

Question 15

What is the consequence between a node and its predecessors while creating Bayesian network?

A)conditionally dependent
B)dependent
C)conditionally independent
D)both a & b

Question 16

How many terms are required for building a Bayesian model?

A)1
B)2
C)3
D)4

Question 17

What is needed to make probabilistic systems feasible in the world?

A)reliability
B)crucial robustness
C)feasibility
D)none of the mentioned

Question 18

How the entries in the full joint probability distribution can be calculated?

A)using variables
B)using information
C)both a & b
D)none of the mentioned

Question 19

How the Bayesian network can be used to answer any query?

A)full distribution
B)joint distribution
C)partial distribution
D)all of the mentioned

Question 20

How the compactness of the Bayesian network can be described?

A)locally structured
B)fully structured
C)partial structure
D)all of the mentioned

Question 21

To which does the local structure is associated?

A)hybrid
B)dependent
C)linear
D)none of the mentioned

Question 22

Elementary linguistic units which are smaller than words are:

A)allophones
B)phonemes
C)syllables
D)all of the mentioned

Question 23

In LISP, the atom that stands for "true" is

A)t
B)ml
C)y
D)time

Question 24

A mouse device may be:

A)electro-chemical
B)mechanical
C)optical
D)both b and c