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Welcome to the Feedforward Neural Networks MCQs Page

Dive deep into the fascinating world of Feedforward Neural Networks with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Feedforward Neural Networks, a crucial aspect of Neural Networks. In this section, you will encounter a diverse range of MCQs that cover various aspects of Feedforward Neural Networks, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Neural Networks.

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Check out the MCQs below to embark on an enriching journey through Feedforward Neural Networks. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Neural Networks.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Feedforward Neural Networks. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Feedforward Neural Networks MCQs | Page 6 of 9

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Q51.
What is a mapping problem?

a.

when no restrictions such as linear separability is placed on the set of input – output pattern pairs

b.

when there may be restrictions such as linear separability placed on input – output patterns

c.

when there are restriction but other than linear separability

d.

none of the mentioned

Discuss
Answer: (a).when no restrictions such as linear separability is placed on the set of input – output pattern pairs
Q52.
Can mapping problem be a more general case of pattern classification problem?

a.

YES

b.

NO

c.

May be YES or NO

d.

Can't Say

Discuss
Answer: (a).YES
Q53.
What is the objective of pattern mapping problem?

a.

to capture weights for a link

b.

to capture inputs

c.

to capture feedbacks

d.

to capture implied function

Discuss
Answer: (d).to capture implied function
Q54.
To provide generalization capability to a network, what should be done?

a.

all units should be linear

b.

all units should be non – linear

c.

except input layer, all units in other layers should be non – linear

d.

none of the mentioned

Discuss
Answer: (c).except input layer, all units in other layers should be non – linear
Q55.
Does an approximate system produce strictly an interpolated output?

a.

YES

b.

NO

c.

May be YES or NO

d.

Can't Say

Discuss
Answer: (b).NO
Q56.
The nature of mapping problem decides?

a.

number of units in second layer

b.

number of units in third layer

c.

overall number of units in hidden layers

d.

none of the mentioned

Discuss
Answer: (c).overall number of units in hidden layers
Q57.
How is hard learning problem solved?

a.

using nonlinear differentiable output function for output layers

b.

using nonlinear differentiable output function for hidden layers

c.

using nonlinear differentiable output function for output and hidden layers

d.

it cannot be solved

Discuss
Answer: (c).using nonlinear differentiable output function for output and hidden layers
Q58.
The number of units in hidden layers depends on?

a.

the number of inputs

b.

the number of outputs

c.

both the number of inputs and outputs

d.

the overall characteristics of the mapping problem

Discuss
Answer: (d).the overall characteristics of the mapping problem
Q59.
From given input-output pairs pattern recognition model should capture characteristics of the system?

a.

True

b.

False

c.

May be True or False

d.

Can't Say

Discuss
Answer: (a).True
Q60.
Let a(l), b(l) represent in input-output pairs, where “l” varies in natural range of no.s, then if a(l)=b(l)?

a.

problem is heteroassociation

b.

problem is autoassociation

c.

can be either auto or heteroassociation

d.

none of the mentioned

Discuss
Answer: (b).problem is autoassociation
Page 6 of 9

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