Neural Network Questions and Answers – Boltzman Machine – 2

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This set of Neural Networks Multiple Choice Questions & Answers focuses on “Boltzman Machine – 2”.

1. For what purpose Feedback neural networks are primarily used?
a) classification
b) feature mapping
c) pattern mapping
d) none of the mentioned
View Answer

Answer: d
Explanation: Feedback neural networks are primarily used for pattern storage.
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2. Presence of false minima will have what effect on probability of error in recall?
a) directly
b) inversely
c) no effect
d) directly or inversely
View Answer

Answer: a
Explanation: Presence of false minima will increase the probability of error in recall.

3. How is effect false minima reduced
a) deterministic update of weights
b) stochastic update of weights
c) deterministic or stochastic update of weights
d) none of the mentioned
View Answer

Answer: b
Explanation: Presence of false minima can be reduced by stochastic update.

4. Is Boltzman law practical for implementation?
a) yes
b) no
View Answer

Answer: b
Explanation: Boltzman law is too slow for implementation.

5. For practical implementation what type of approximation is used on boltzman law?
a) max field approximation
b) min field approximation
c) hopfield approximation
d) none of the mentioned
View Answer

Answer: d
Explanation: For practical implementation mean field approximation is used.
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6. What happens when we use mean field approximation with boltzman learning?
a) it slows down
b) it get speeded up
c) nothing happens
d) may speedup or speed down
View Answer

Answer: b
Explanation: Boltzman learning get speeded up using mean field approximation.

7. Approximately how much times the boltzman learning get speeded up using mean field approximation?
a) 5-10
b) 10-30
c) 30-50
d) 50-70
View Answer

Answer: b
Explanation: Boltzman learning get speeded up 10-30 using mean field approximation.

8.False minima can be reduced by deterministic updates?
a) yes
b) no
View Answer

Answer: b
Explanation: Presence of false minima can be reduced by stochastic update.

9. In boltzman learning which algorithm can be used to arrive at equilibrium?
a) hopfield
b) mean field
c) hebb
d) none of the mentioned
View Answer

Answer: d
Explanation: Metropolis algorithm can be used to arrive at equilibrium.

10. Boltzman learning is a?
a) fast process
b) steady process
c) slow process
d) none of the mentioned
View Answer

Answer: d
Explanation: Boltzman learning is a slow process.
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Sanfoundry Global Education & Learning Series – Neural Networks.

To practice all areas of Neural Networks, here is complete set on 1000+ Multiple Choice Questions and Answers.

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He is Linux Kernel Developer & SAN Architect and is passionate about competency developments in these areas. He lives in Bangalore and delivers focused training sessions to IT professionals in Linux Kernel, Linux Debugging, Linux Device Drivers, Linux Networking, Linux Storage, Advanced C Programming, SAN Storage Technologies, SCSI Internals & Storage Protocols such as iSCSI & Fiber Channel. Stay connected with him @ LinkedIn