Artificial Intelligence MCQs with Answers
Practice important Artificial Intelligence MCQs with answers and explanations.
Chapter: 38
Q1181:
The entropy of a subset is 0 if:
A. All examples are negative
B. All examples are positive
C. All examples are same class
D. All of the above
Correct Answer:
D
Chapter: 38
Q1182:
Fill in the blank: ________ is used to select the root node in ID3.
A. GAIN
B. INFO
C. PURITY
D. DEPTH
Correct Answer:
A
Chapter: 38
Q1183:
Fill in the blank: The entropy formula contains the terms ______ and ______.
A. p+, p-
B. p+, n-
C. x+, x-
D. y+, y-
Correct Answer:
A
Chapter: 38
Q1184:
What does ID3 do when an attribute gives the highest information gain?
A. Skips it
B. Assigns it as leaf
C. Adds it as root
D. Removes it from list
Correct Answer:
C
Chapter: 38
Q1185:
The attribute B had what information gain value in the full dataset S?
A. 0.02
B. 0.57
C. 0.97
D. 1
Correct Answer:
A
Chapter: 38
Q1186:
What was the gain for E in the full dataset?
A. 0.57
B. 0.02
C. 0.5
D. 1
Correct Answer:
B
Chapter: 38
Q1187:
Which attribute was chosen next after splitting with A in the decision tree?
A. B
B. A
C. E
D. None of these
Correct Answer:
A
Chapter: 38
Q1188:
How many records were left to classify after initial split on A?
A. 1
B. 3
C. 2
D. 4
Correct Answer:
C
Chapter: 38
Q1189:
Fill in the blank: After splitting using A, a2 still had ________ in output classification.
A. Mixed values
B. Only YES
C. Only NO
D. Unknown
Correct Answer:
A
Chapter: 38
Q1190:
Which formula is used to calculate entropy for subsets of data?
A. E(Sa) = -p+log2p+ - p-log2p-
B. E(Sa) = S/N
C. E(Sa) = Gain/Total
D. E(Sa) = p+/p-
Correct Answer:
A
Chapter: 38
Q1191:
If gain for attribute B in subset S’ is 0, what does it indicate?
A. B is very informative
B. B perfectly splits the data
C. B has no information gain
D. B has max entropy
Correct Answer:
C
Chapter: 38
Q1192:
Which of the following does NOT affect entropy?
A. Number of examples
B. Positive/Negative ratio
C. Log base used
D. Attribute name
Correct Answer:
D
Chapter: 38
Q1193:
Fill in the blank: ID3 constructs a _______ tree based on information gain.
A. Binary
B. Decision
C. Spanning
D. Search
Correct Answer:
B
Chapter: 39
Q1194:
Which learning paradigm is inspired by biology and involves a network of parallel distributed computing?
A. Decision Trees
B. Artificial Neural Networks
C. Support Vector Machines
D. Genetic Algorithms
Correct Answer:
B
Chapter: 39
Q1195:
What tasks are well suited for the connectionist approach in artificial neural networks?
A. Classification and Pattern Recognition
B. Only Prediction
C. Only Data Storage
D. Only Image Editing
Correct Answer:
A
Chapter: 39
Q1196:
The process where several weak signals combine to form a single large signal in a neuron is called ________.
A. Spatial summation
B. Temporal summation
C. Synaptic transmission
D. Axon firing
Correct Answer:
A
Chapter: 39
Q1197:
Temporal summation in neurons converts ________.
A. Multiple weak signals from different sources into one large signal
B. A rapid series of weak pulses from one source into one large signal
C. One strong pulse into several weak signals
D. None of the above
Correct Answer:
B
Chapter: 39
Q1198:
The axon hillock in a neuron decides whether the neuron will fire based on whether the input exceeds the ________.
A. Threshold value
B. Synapse
C. Neuron cell body
D. Dendritic tree
Correct Answer:
A
Chapter: 39
Q1199:
What is the function of the soma in a neuron?
A. Signal processing
B. Signal transmission
C. Maintenance of neuron functionality
D. Generating output signal
Correct Answer:
C
Chapter: 39
Q1200:
Biological Neural Networks are generally ________ compared to computers.
A. Slower but more fault tolerant
B. Faster but less fault tolerant
C. Slower and less fault tolerant
D. Faster and more fault tolerant
Correct Answer:
A