MCQOPTIONS
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MCQOPTIONS
This section includes 12 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
How can learning process be stopped in backpropagation rule? |
| A. | there is convergence involved |
| B. | no heuristic criteria exist |
| C. | on basis of average gradient value |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 2. |
Does backpropagaion learning is based on gradient descent along error surface? |
| A. | yes |
| B. | no |
| C. | cannot be said |
| D. | it depends on gradient descent but not error surface |
| Answer» B. no | |
| 3. |
What is meant by generalized in statement “backpropagation is a generalized delta rule” ? |
| A. | because delta rule can be extended to hidden layer units |
| B. | because delta is applied to only input and output layers, thus making it more simple and generalized |
| C. | it has no significance |
| D. | none of the mentioned |
| Answer» B. because delta is applied to only input and output layers, thus making it more simple and generalized | |
| 4. |
DOES_BACKPROPAGAION_LEARNING_IS_BASED_ON_GRADIENT_DESCENT_ALONG_ERROR_SURFACE??$ |
| A. | yes |
| B. | no |
| C. | cannot be said |
| D. | it depends on gradient descent but not error surface |
| Answer» B. no | |
| 5. |
How_can_learning_process_be_stopped_in_backpropagation_rule?$ |
| A. | there is convergence involved |
| B. | no heuristic criteria exist |
| C. | on basis of average gradient value |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 6. |
What are the general tasks that are performed with backpropagation algorithm? |
| A. | pattern mapping |
| B. | function approximation |
| C. | prediction |
| D. | all of the mentioned |
| Answer» E. | |
| 7. |
What are general limitations of back propagation rule? |
| A. | local minima problem |
| B. | slow convergence |
| C. | scaling |
| D. | all of the mentioned |
| Answer» E. | |
| 8. |
What is meant by generalized in statement “backpropagation is a generalized delta rule” ?$ |
| A. | because delta rule can be extended to hidden layer units |
| B. | because delta is applied to only input and output layers, thus making it more simple and generalized |
| C. | it has no significance |
| D. | none of the mentioned |
| Answer» B. because delta is applied to only input and output layers, thus making it more simple and generalized | |
| 9. |
There is feedback in final stage of backpropagation algorithm? |
| A. | yes |
| B. | no |
| Answer» C. | |
| 10. |
What is true regarding backpropagation rule? |
| A. | it is also called generalized delta rule |
| B. | error in output is propagated backwards only to determine weight updates |
| C. | there is no feedback of signal at nay stage |
| D. | all of the mentioned |
| Answer» E. | |
| 11. |
The backpropagation law is also known as generalized delta rule, is it true? |
| A. | yes |
| B. | no |
| Answer» B. no | |
| 12. |
What is the objective of backpropagation algorithm? |
| A. | to develop learning algorithm for multilayer feedforward neural network |
| B. | to develop learning algorithm for single layer feedforward neural network |
| C. | to develop learning algorithm for multilayer feedforward neural network, so that network can be trained to capture the mapping implicitly |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |