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
Explanation: Feedback neural networks are primarily used for pattern storage.
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
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
Explanation: Presence of false minima can be reduced by stochastic update.
4. Is Boltzman law practical for implementation?
a) yes
b) no
View Answer
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
Explanation: For practical implementation mean field approximation is used.
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
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
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
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
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
Explanation: Boltzman learning is a slow process.
Sanfoundry Global Education & Learning Series – Neural Networks.
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