NPTEL Data Mining Week 4 Assignment Answers 2025
1. Maximum aposteriori classifier is also known as:
A. Decision tree classifier
B. Bayes classifier
C. Gaussian classifier
D. Maximum margin classifier
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2. If we are provided with an infinite sized training set which of the following classifier will have the lowest error probability?
A. Decision tree
B. K- nearest neighbor classifier
C. Bayes classifier
D. Support vector machine
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3. Let A be an example, and C be a class. The probability P(C|A) is known as:
A. Apriori probability
B. Aposteriori probability
C. Class conditional probability
D. None of the above
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4. Let A be an example, and C be a class. The probability P(C) is known as:
A. Apriori probability
B. Aposteriori probability
C. Class conditional probability
D. None of the above
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5. A bank classifies its customer into two classes “fraud” and “normal” based on their installment payment behavior. We know that the probability of a customer being being fraud is P(fraud) = 0.20, the probability of customer defaulting installment payment is P(default) = 0.40, and the probability that a fraud customer defaults in installment payment is P(default|fraud) = 0.80. What is the probability of a customer who defaults in payment being a fraud?
A. 0.80
B. 0.60
C. 0.40
D. 0.20
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6. Consider two binary attributes X and Y. We know that the attributes are independent and probability P(X=1) = 0.6, and P(Y=0) = 0.4. What is the probability that both X and Yhave values 1?
A. 0.06
B. 0.16
C. 0.26
D. 0.36
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7. Consider a binary classification problem with two classes C1 and C2. Class labels of ten other training set instances sorted in increasing order of their distance to an instance x is as follows: {C1, C2, C1, C2, C2, C2, C1, C2, C1, C2}. How will a K=7 nearest neighbor classifier classify x?
A. There will be a tie
B. C1
C. C2
D. Not enough information to classify
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8. 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. What is the estimated apriori probability P(fraud)of the class fraud?
A. 0.2
B. 0.4
C. 0.6
D. 0.8
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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. What is the estimated class conditional probability P(A1=1, A2=1|fraud)?
A. 0.25
B. 0.50
C. 0.75
D. 1.00
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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. The Bayes classifier classifies the instance (A1=1, A2=1) into class?
A. fraud
B. normal
C. there will be a tie
D. not enough information to classify
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