McqMate
These multiple-choice questions (MCQs) are designed to enhance your knowledge and understanding in the following areas: Master of Science in Computer Science (MSc CS) .
| 51. |
A _________ is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. |
| A. | decision tree |
| B. | graphs |
| C. | trees |
| D. | neural networks |
| Answer» A. decision tree | |
| 52. |
Decision Tree is |
| A. | flow-chart |
| B. | structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label |
| C. | both a) & b) |
| D. | none of the mentioned |
| Answer» C. both a) & b) | |
| 53. |
How many types of learning are available in machine learning? |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» C. 3 | |
| 54. |
Choose from the following that are Decision Tree nodes |
| A. | decision nodes |
| B. | weighted nodes |
| C. | chance nodes |
| D. | end nodes |
| Answer» D. end nodes | |
| 55. |
Decision Nodes are represented by, |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» B. squares | |
| 56. |
Chance Nodes are represented by, |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» C. circles | |
| 57. |
End Nodes are represented by, |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» D. triangles | |
| 58. |
How the decision tree reaches its decision? |
| A. | single test |
| B. | two test |
| C. | sequence of test |
| D. | no test |
| Answer» C. sequence of test | |
| 59. |
What is the other name of informed search strategy? |
| A. | simple search |
| B. | heuristic search |
| C. | online search |
| D. | none of the mentioned |
| Answer» B. heuristic search | |
| 60. |
How many types of informed search method are in artificial intelligence? |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» D. 4 | |
| 61. |
Which function will select the lowest expansion node atfirst for evaluation? |
| A. | greedy best-first search |
| B. | best-first search |
| C. | both a & b |
| D. | none of the mentioned |
| Answer» B. best-first search | |
| 62. |
What is the heuristic function of greedy best-first search? |
| A. | f(n) != h(n) |
| B. | f(n) < h(n) |
| C. | f(n) = h(n) |
| D. | f(n) > h(n) |
| Answer» C. f(n) = h(n) | |
| 63. |
Which search uses only the linear space for searching? |
| A. | best-first search |
| B. | recursive best-first search |
| C. | depth-first search |
| D. | none of the mentioned |
| Answer» B. recursive best-first search | |
| 64. |
Which method is used to search better by learning? |
| A. | best-first search |
| B. | depth-first search |
| C. | metalevel state space |
| D. | none of the mentioned |
| Answer» C. metalevel state space | |
| 65. |
Which search is complete and optimal when h(n) is consistent? |
| A. | best-first search |
| B. | depth-first search |
| C. | both a & b |
| D. | a* search |
| Answer» D. a* search | |
| 66. |
Which is used to improve the performance of heuristic search? |
| A. | quality of nodes |
| B. | quality of heuristic function |
| C. | simple form of nodes |
| D. | none of the mentioned |
| Answer» B. quality of heuristic function | |
| 67. |
Which search method will expand the node that is closest to the goal? |
| A. | best-first search |
| B. | greedy best-first search |
| C. | a* search |
| D. | none of the mentioned |
| Answer» B. greedy best-first search | |
| 68. |
Which data structure is used to give better heuristic estimates? |
| A. | forwards state-space |
| B. | backward state-space |
| C. | planning graph algorithm |
| D. | none of the mentioned |
| Answer» C. planning graph algorithm | |
| 69. |
Which is used to extract solution directly from the planning graph? |
| A. | planning algorithm |
| B. | graph plan |
| C. | hill-climbing search |
| D. | all of the mentioned |
| Answer» B. graph plan | |
| 70. |
What are present in the planning graph? |
| A. | sequence of levels |
| B. | literals |
| C. | variables |
| D. | heuristic estimates |
| Answer» A. sequence of levels | |
| 71. |
What is the starting level of planning graph? |
| A. | level 3 |
| B. | level 2 |
| C. | level 1 |
| D. | level 0 |
| Answer» D. level 0 | |
| 72. |
What are present in each level of planning graph? |
| A. | literals |
| B. | actions |
| C. | variables |
| D. | both a & b |
| Answer» D. both a & b | |
| 73. |
Which kind of problem is suitable for planning graph? |
| A. | propositional planning problem |
| B. | planning problem |
| C. | action problem |
| D. | none of the mentioned |
| Answer» A. propositional planning problem | |
| 74. |
What is meant by persistence actions? |
| A. | allow a literal to remain false |
| B. | allow a literal to remain true |
| C. | both a & b |
| D. | none of the mentioned |
| Answer» B. allow a literal to remain true | |
| 75. |
When will further expansion is unnecessary for planning graph? |
| A. | identical |
| B. | replicate |
| C. | not identical |
| D. | none of the mentioned |
| Answer» A. identical | |
| 76. |
How many conditions are available between two actions in mutex relation? |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» C. 3 | |
| 77. |
What is called inconsistent support? |
| A. | if two literals are not negation of other |
| B. | if two literals are negation of other |
| C. | mutually exclusive |
| D. | none of the mentioned |
| Answer» B. if two literals are negation of other | |
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