
XAI - Assignment II
Authored by T.SAKTHI IT
Computers
University
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20 questions
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1.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
Which of the following statements is not true about the Decision tree?
It can be applied on binary classification problems only
It is a predictor that predicts the label associated with an instance by traveling from a root node of a tree to a leaf
At each node, the successor child is chosen on the basis of a splitting of the input space
The splitting is based on one of the features or on a predefined set of splitting rules
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Consider the figure. If person A starts driving at 8:30 AM and there are no other vehicles on the road, and another person B starts driving at 10 AM and there is an accident on the road, what will be the commute time of A and B respectively?
LONG, LONG
LONG, SHORT
SHORT, LONG
SHORT, SHORT
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does the following figure represent?
Decision tree for OR
Decision tree for AND
Decision tree for XOR
Decision tree for XNOR
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main advantage of using the Random Forest algorithm?
It always gives 100% accuracy
It reduces overfitting and improves generalization
It requires only one decision tree for better performance
It works only for classification problems
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does Random Forest prevent overfitting?
By using a single deep decision tree
By selecting all features at each split
By averaging predictions from multiple trees trained on different subsets of data
By using only the most important features
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does Random Forest select features at each split in a tree?
It considers all features every time
It uses only the most correlated features
It removes features with missing values
It selects a random subset of features
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a key characteristic of Random Forest?
It requires extensive data preprocessing
It works only with numerical data
It is a supervised learning algorithm
It cannot handle missing values
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