Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Multiple Choice Questions
Q1161: Decision trees represent knowledge in the form of
- A: Graphs
- B: Rules
- C: Tables
- D: Trees
View Answer
D
Q1162: Minimal generalization is applied to S set when example is
- A: Positive
- B: Negative
- C: Irrelevant
- D: Test
View Answer
A
Q1163: Minimal specialization is applied to G set when example is
- A: Positive
- B: Negative
- C: Irrelevant
- D: Test
View Answer
B
Q1164: The purpose of Candidate-Elimination is to find
- A: All possible consistent hypotheses
- B: The most general hypothesis
- C: The simplest hypothesis
- D: The first matching example
View Answer
A
Q1165: The first hypothesis in S set is usually
- A: Most specific
- B: Most general
- C: Random
- D: None
View Answer
A
Q1166: In Candidate-Elimination, training examples are processed
- A: Once
- B: Multiple times
- C: Only negative
- D: Only positive
View Answer
A
Q1167: What does ID3 stand for?
- A: Incremental Dichotomizer 3
- B: Iterative Decision Design
- C: Interactive Dichotomizer 3
- D: Information Depth 3
View Answer
C
Q1168: Which step is performed first in the ID3 algorithm?
- A: Build leaf nodes
- B: Calculate entropy
- C: Find the root node
- D: Choose the attribute with least value
View Answer
C
Q1169: What is the primary function used in ID3 to evaluate attributes?
- A: ENTROPY()
- B: FIND()
- C: GAIN()
- D: INFO()
View Answer
C
Q1170: Which attribute becomes the root node in ID3?
- A: Attribute with least entropy
- B: Random attribute
- C: Attribute with highest frequency
- D: Attribute with maximum information gain
View Answer
D