NPTEL Data Mining Week 3 Assignment Answers 2025
1. Decision tree is an algorithm for:
A. Classification
B. Clustering
C. Association rule mining
D. Noise filtering
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2. Leaf nodes of a decision tree correspond to:
A. Attributes
B. Classes
C. Data instances
D. None of the above
Answer :-
3. Non-leaf nodes of a decision tree correspond to:
A. Attributes
B. Classes
C. Data instances
D. None of the above
Answer :-
4. Which of the following criteria is used to decide which attribute to split next ina decision tree:
A. Support
B. Confidence
C. Entropy
D. Scatter
Answer :-
5. If we convert a decision tree to a set of logical rules, then:
A. the internal nodes in a branch are connected by AND and the branches by AND
B. the internal nodes in a branch are connected by OR and the branches by OR
C. the internal nodes in a branch are connected by AND and the branches by OR
D. the internal nodes in a branch are connected by OR and the branches by AND
Answer :-
6. The purpose of pruning a decision tree is:
A. improving training set classification accuracy
B. improving generalization performance
C. dimensionality reduction
D. tree balancing
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7. Given the following training set for classification problem into two classes “fraud” and “normal”. There are two attributes A1 and A2 taking values 0 or 1. Splitting on which attribute in the root of a decision tree will lead to highest information gain?
A. A1
B. A2
C. There will be a tie among the attributes
D. Not enough information to decide
Answer :-
8.
A. 0
B. –(4/10)xlog(4/10)-(6/10)xlog(6/10)
C. –log(4/10)-log(6/10)
D. 1
Answer :-
9. Given the following training set for classification problem into two classes “fraud” and “normal”. There are two attributes A1 and A2 taking values 0 or 1. Splitting on attribute A1 in the root leads to an entropy reduction of?
A. –log(4/10)-log(6/10)
B. –(4/10)xlog(4/10)-(6/10)xlog(6/10) + (4/7)xlog(4/7) + (3/7)xlog(3/7)
C. –(4/10)xlog(4/10)-(6/10)xlog(6/10) + (4/7)xlog(4/7) + (3/7)xlog(3/7) + 1
D. 1
Answer :-
10. Given the following training set for classification problem into two classes “fraud” and “normal”. There are two attributes A1 and A2 taking values 0 or 1. Splitting on attribute A2 in the root leads to an entropy reduction of?
A. –log(4/10)-log(6/10)
B. –(4/10)xlog(4/10)-(6/10)xlog(6/10) + (1/4)xlog(1/4) + (3/7)xlog(3/7)
C. –(4/10)xlog(4/10)-(6/10)xlog(6/10) + (3/4)xlog(3/4) + (1/4)xlog(1/4) + (1/6)xlog(1/6) +(5/6)xlog(5/6)
D. 1
Answer :-
11. Decision trees can be used for:
A. Classification only
B. Regression only
C. Both classification and regression
D. Neither of classification and regression
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