Question:

____________ 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

Answer» c. fuzzy set

Question:

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

A.

fuzzy logic

B.

probability

C.

entropy

D.

all of the mentioned

Answer» d. all of the mentioned

Question:

How many terms are required for building a Bayesian model?

A.

1

B.

2

C.

3

D.

4

Answer» c. 3

Question:

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

Answer» b. using information

Question:

To which does the local structure is associated?

A.

hybrid

B.

dependent

C.

linear

D.

none of the mentioned

Answer» c. linear

Question:

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

Answer» c. conditionally independent

Question:

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

A.

reliability

B.

crucial robustness

C.

feasibility

D.

none of the mentioned

Answer» b. crucial robustness

Question:

Fuzzy logic is usually represented as

A.

if-then-else rules

B.

if-then rules

C.

both a & b

D.

none of the mentioned

Answer» b. if-then rules

Question:

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

Answer» a. complete description of the domain

Question:

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

Answer» b. joint distribution