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This section includes 10 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks Question and Answers Pattern Classification 2 knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
If the output produces nonconvex regions, then how many layered neural is required at minimum? |
| A. | 2 |
| B. | 3 |
| C. | 4 |
| D. | 5 |
| Answer» D. 5 | |
| 2. |
Intersection of convex regions in three layer network can only produce convex surfaces, is the statement true? |
| A. | yes |
| B. | no |
| Answer» C. | |
| 3. |
Intersection of linear hyperplanes in three layer network can only produce convex surfaces, is the statement true? |
| A. | yes |
| B. | no |
| Answer» B. no | |
| 4. |
In a three layer network, number of classes is determined by? |
| A. | number of units in second layer |
| B. | number of units in third layer |
| C. | number of units in second and third layer |
| D. | none of the mentioned |
| Answer» C. number of units in second and third layer | |
| 5. |
In a three layer network, shape of dividing surface is determined by? |
| A. | number of units in second layer |
| B. | number of units in third layer |
| C. | number of units in second and third layer |
| D. | none of the mentioned |
| Answer» B. number of units in third layer | |
| 6. |
As dimensionality of input vector increases, what happens to linear separability? |
| A. | increases |
| B. | decreases |
| C. | no effect |
| D. | doesn t depend on dimensionality |
| Answer» C. no effect | |
| 7. |
If pattern classes are linearly separable then hypersurfaces reduces to straight lines? |
| A. | yes |
| B. | no |
| Answer» B. no | |
| 8. |
Is it true that percentage of linearly separable functions will increase rapidly as dimension of input pattern space is increased? |
| A. | yes |
| B. | no |
| Answer» C. | |
| 9. |
When line joining any two points in the set lies entirely in region enclosed by the set in M-dimensional space , then the set is known as? |
| A. | convex set |
| B. | concave set |
| C. | may be concave or convex |
| D. | none of the mentioned |
| Answer» B. concave set | |
| 10. |
Convergence in perceptron learning takes place if and only if: |
| A. | a minimal error condition is satisfied |
| B. | actual output is close to desired output |
| C. | classes are linearly separable |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |