Hello NPTEL Learners, In this article, you will find **NPTEL Data Mining Assignment 3 Week 3 Answers 2023**. All the Answers are provided below to help the students as a reference donâ€™t straight away look for the solutions, first try to solve the questions by yourself. If you find any difficulty, then look for the solutions.

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## NPTEL Data Mining Assignment 3 Answers 2023:

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#### Q.1. Internal nodes of a decision tree correspond to:

#### Q.2. In a multiclass classification problem, Bayes classifier assigns an instance to the class corresponding to:

**A. Highest aposteriori probability**- B. Highest apriori probability
- C. Lowest aposteriori probability
- D. A. Lowest apriori probability

#### Q.3. Three identical bags contain blue and yellow balls. The first bag contains 3 blue and 2 yellow balls, the second bag has 4 blue and 5 yellow balls, and the third bag has 2 blue and 4 yellow balls. A bag is chosen randomly and a ball is chosen from it. If the ball that is drawn out is blue, what will be the probability that the second bag is chosen?

- A. 15/62
- B. 27/62
**C. 10/31**- D. None of the above

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#### Q.4. What is the entropy of the dataset?

- A. 0.50
**B. 0.94**- C. 1
- D. 0

#### Q.5.** **Which attribute would information gain choose as the root of the tree?

#### Q.6. Whether a person will buy if (Age=35, Student-No, Income Low, Credit_rating = Fair)?

**A. Yes**- B. No
- C. The example canâ€™t be classified
- D. Both classes are equally likely.

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#### Q.7. What class does the person(Age-42, Student-No, Income-Medium, Credit_rating = Excellent)?

#### Q.8. What class does the person (Age 25, Student-No, Income-Medium, Credit_rating = Fair}?

- A. Yes
**B. No**- C. The example canâ€™t be classified
- D. Both classes are equally likely

#### Q.9. Which attribute would information gain choose for Age=31-40?

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#### About NPTEL Data Mining Course:

Data mining is study of algorithms for finding patterns in large data sets. It is an integral part of modern industry, where data from its operations and customers are mined for gaining business insight. It is also important in modern scientific endeavors. Data mining is an interdisciplinary topic involving, databases, machine learning and algorithms. The course will cover the fundamentals of data mining. It will explain the basic algorithms like data preprocessing, association rules, classification, clustering, sequence mining and visualization. It will also explain implementations in open source software. Finally, case studies on industrial problems will be demonstrated.

#### Course Layout:

**Week 1:**Â Introduction, Data PreprocessingÂ**Week 2:**Â Association Rule Mining, Classification Basics**Week 3:**Â Decision Tree, Bayes Classifier, K nearest neighborÂ**Week 4:**Support Vector Machine, Kernel MachineÂ**Week 5:**Â Clustering, Outlier detectionÂ**Week 6:**Â Sequence miningÂ**Week 7:Â**Evaluation, Visualization.Â**Week 8:**Â Case studiesÂ

**CRITERIA TO GET A CERTIFICATE**:

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.

Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

**YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.**

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