MCQOPTIONS
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MCQOPTIONS
This section includes 14 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. |
Use of nonlinear units in the feedback layer of competitive network leads to concept of? |
| A. | feature mapping |
| B. | pattern storage |
| C. | pattern classification |
| D. | none of the mentioned |
| Answer» E. | |
| 2. |
What is true for competitive learning? |
| A. | nodes compete for inputs |
| B. | process leads to most efficient neural representation of input space |
| C. | typical for unsupervised learning |
| D. | all of the mentioned |
| Answer» E. | |
| 3. |
What is true regarding adaline learning algorithm |
| A. | uses gradient descent to determine the weight vector that leads to minimal error |
| B. | error is defined as MSE between neurons net input and its desired output |
| C. | this technique allows incremental learning |
| D. | all of the mentioned |
| Answer» E. | |
| 4. |
In feature maps, when weights are updated for winning unit and its neighbour, which type learning it is known as? |
| A. | karnaugt learning |
| B. | boltzman learning |
| C. | kohonen’s learning |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 5. |
USE_OF_NONLINEAR_UNITS_IN_THE_FEEDBACK_LAYER_OF_COMPETITIVE_NETWORK_LEADS_TO_CONCEPT_OF??$ |
| A. | feature mapping |
| B. | pattern storage |
| C. | pattern classification |
| D. | none of the mentioned |
| Answer» E. | |
| 6. |
WHAT_IS_TRUE_FOR_COMPETITIVE_LEARNING??$ |
| A. | nodes compete for inputs |
| B. | process leads to most efficient neural representation of input space |
| C. | typical for unsupervised learning |
| D. | all of the mentioned |
| Answer» E. | |
| 7. |
What is true regarding adaline learning algorith? |
| A. | uses gradient descent to determine the weight vector that leads to minimal error |
| B. | error is defined as MSE between neurons net input and its desired output |
| C. | this technique allows incremental learning |
| D. | all of the mentioned |
| Answer» E. | |
| 8. |
In self organizing network, how is layer connected to output layer? |
| A. | some are connected |
| B. | all are one to one connected |
| C. | each input unit is connected to each output unit |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 9. |
In feature maps, when weights are updated for winning unit and its neighbour, which type learning it is known as? |
| A. | karnaugt learning |
| B. | boltzman learning |
| C. | kohonen’s learning |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 10. |
How are weights updated in feature maps? |
| A. | updated for winning unit only |
| B. | updated for neighbours of winner only |
| C. | updated for winning unit and its neighbours |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| 11. |
What is the objective of feature maps? |
| A. | to capture the features in space of input patterns |
| B. | to capture just the input patterns |
| C. | update weights |
| D. | to capture output patterns |
| Answer» B. to capture just the input patterns | |
| 12. |
How is feature mapping network distinct from competitive learning network? |
| A. | geometrical arrangement |
| B. | significance attached to neighbouring units |
| C. | nonlinear units |
| D. | none of the mentioned |
| Answer» E. | |
| 13. |
In pattern clustering, does physical location of a unit relative to other unit has any significance? |
| A. | yes |
| B. | no |
| C. | depends on type of clustering |
| D. | none of the mentioned |
| Answer» C. depends on type of clustering | |
| 14. |
What kind of learning is involved in pattern clustering task? |
| A. | supervised |
| B. | unsupervised |
| C. | learning with critic |
| D. | none of the mentioned |
| Answer» C. learning with critic | |