UGC NET · PAPER 2
UGC NET Paper 2 Computer Science – Unit 10: Artificial Intelligence (AI) PYQ (December 2022 Shift 1)
Q16. If we convert a decision tree into a set of logical rules, then:
- The internal nodes in a branch are connected by AND and branches by AND
- The internal nodes in a branch are connected by OR and branches by OR
- The internal nodes in a branch are connected by AND and branches by OR
- The internal nodes in a branch are connected by OR and branches by AND
Q37. Which search technique is complete and optimal when h(n) is consistent?
- Best-first search
- Depth-first search
- A* search
- Breadth-first search
Q38. The process of capturing an inference process as a single inference rule is called:
- Ponens
- Clauses
- Generalized modus ponens
- Variables
Q39. Fuzzy logic is a form of ____
- Two-valued logic
- Crisp set logic
- Binary set logic
- Many-valued logic
Q40. The 4Ws problem canvas helps in identifying the key elements related to the problem. The 4Ws problem canvas is a part of ____
- Problem scoping
- Data acquisition
- Data modelling
- Problem evaluation
Q64. Consider the following features of neural networks:
A. It is essentially a machine-learning algorithm.
B. It is useful for problems where the data set is very large.
C. It can extract features without input from the programmer.
D. It is a system modelled on the human brain and nervous system.
Choose the most appropriate answer from the options given below:
A. It is essentially a machine-learning algorithm.
B. It is useful for problems where the data set is very large.
C. It can extract features without input from the programmer.
D. It is a system modelled on the human brain and nervous system.
Choose the most appropriate answer from the options given below:
- A Only
- A & B Only
- A, B & C Only
- A, B, C & D
Q65. Consider the following drawbacks of the rule-based approach:
A. The learning is static.
B. Changes made to the original data are not considered.
C. Once trained, the model cannot improve on the basis of feedback.
A. The learning is static.
B. Changes made to the original data are not considered.
C. Once trained, the model cannot improve on the basis of feedback.
- All the above statements are correct
- Statements A & B only are not correct
- Statements B & C only are not correct
- All the above statements are not correct
Q75. Match List I with List II (I. Unsupervised learning, II. Supervised learning): A. Regression, B. KNN, C. Clustering, D. Decision Tree
- A-I, B-II, C-I, D-II
- A-II, B-II, C-I, D-II
- A-I, B-II, C-II, D-I
- A-II, B-II, C-II, D-I
Q82. Consider the weighted directed graph with edges A→C (2), A→F (7), C→B (10), C→F (3), B→D (1), B→Z (15), F→D (1), F→E (6), D→Z (7), D→E (2), E→Z (4). In what order are the nodes traversed to find the shortest path from A to Z?
- A → C → F → D → E
- A → C → E → B
- A → C → F → E → B
- A → C → D → F
Q85. Which of the following describes the flow through the layers of a neural network?
A. Information → Input layer → Hidden layer
B. Bias → Output layer → Hidden layer
C. Hidden layer → Algorithm → Output layer
D. Input layer → Output layer → Algorithms
A. Information → Input layer → Hidden layer
B. Bias → Output layer → Hidden layer
C. Hidden layer → Algorithm → Output layer
D. Input layer → Output layer → Algorithms
- Only sequence A is correct.
- Only sequence B is correct.
- Only sequence C is correct.
- Only sequence D is correct.
Q90. Given below are two statements: one is labelled as Assertion A and the other as Reason R.
A: Artificial neural networks are the backbone of deep-learning algorithms.
R: Back propagation is one of the techniques used to train an ANN.
A: Artificial neural networks are the backbone of deep-learning algorithms.
R: Back propagation is one of the techniques used to train an ANN.
- Both A and R are correct and R is the correct explanation of A.
- Both A and R are correct but R is NOT the correct explanation of A.
- A is correct but R is not correct.
- A is not correct but R is correct.