Neural Network Questions and Answers – Pattern Association – 2

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This set of Neural Networks question bank focuses on “Pattern Association – 2”.

1. What are hard problems?
a) classification problems which are not clearly separable
b) classification problems which are not associatively separable
c) classification problems which are not functionally separable
d) none of the mentioned
View Answer

Answer: d
Explanation: Classification problems which are not linearly separable separable are known as hard problems.

2. In order to overcome constraint of linearly separablity concept of multilayer feedforward net is proposed?
a) yes
b) no
View Answer

Answer: a
Explanation: Multilayer feedforward net with non linear processing units in intermidiate hidden layer is proposed.

3. The hard learning problem is ultimately solved by hoff’s algorithm?
a) yes
b) no
View Answer

Answer: b
Explanation: The hard learning problem is ultimately solved by backpropagation algorithm.
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4. What is generalization?
a) ability to store a pattern
b) ability to recall a pattern
c) ability to learn a mapping function
d) none of the mentioned
View Answer

Answer: c
Explanation: Generalization is the ability to learn a mapping function.

5. Generalization feature of a multilayer feedforward network depends on factors?
a) architectural details
b) learning rate parameter
c) training samples
d) all of the mentioned
View Answer

Answer: a
Explanation: Generalization feature of a multilayer feedforward network depends on all of these above mentioned factors.

6. What is accretive behaviour?
a) not a type of pattern clustering task
b) for small noise variations pattern lying closet to the desired pattern is recalled.
c) for small noise variations noisy pattern having parameter adjusted according to noise variation is recalled
d) none of the mentioned
View Answer

Answer: b
Explanation: In accretive behaviour, pattern lying closet to the desired pattern is recalled.

7. What is Interpolative behaviour?
a) not a type of pattern clustering task
b) for small noise variations pattern lying closet to the desired pattern is recalled.
c) for small noise variations noisy pattern having parameter adjusted according to noise variation is recalled
d) none of the mentioned
View Answer

Answer: c
Explanation: In interpolative behaviour, pattern having parameter adjusted according to noise variation is recalled & not the ideal one.
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8. Does pattern association involves non linear units in feedforward neural network?
a) yes
b) no
View Answer

Answer: b
Explanation: There are only two layers & single set of weights in pattern association.

9. What is the feature that doesn’t belongs to pattern classification in feeddorward neural networks?
a) recall is direct
b) delta rule learning
c) non linear processing units
d) two layers
View Answer

Answer: b
Explanation: It involves perceptron learning.
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10. What is the feature that doesn’t belongs to pattern mapping in feeddorward neural networks?
a) recall is direct
b) delta rule learning
c) non linear processing units
d) two layers
View Answer

Answer: d
Explanation: It involves multiple layers.

Sanfoundry Global Education & Learning Series – Neural Networks.

To practice Neural Networks question bank, here is complete set on 1000+ Multiple Choice Questions and Answers.

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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