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
a) classification problems which are not associatively separable
a) classification problems which are not functionally separable
d) none of the mentioned
View Answer
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
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
Explanation: The hard learning problem is ultimately solved by backpropagation algorithm.
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
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
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
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
Explanation: In interpolative behaviour, pattern having parameter adjusted according to noise variation is recalled & not the ideal one.
8. Does pattern association involves non linear units in feedforward neural network?
a) yes
b) no
View Answer
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
Explanation: It involves perceptron learning.
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
Explanation: It involves multiple layers.
Sanfoundry Global Education & Learning Series – Neural Networks.
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