Exam Details
Subject | data mining | |
Paper | ||
Exam / Course | b.sc.computer science | |
Department | ||
Organization | loyola college | |
Position | ||
Exam Date | November, 2017 | |
City, State | tamil nadu, chennai |
Question Paper
1
LOYOLA COLLEGE (AUTONOMOUS), CHENNAI 600 034
B.Sc.,B.C.A. DEGREE EXAMINATION COMPUTER SCIENCE &COMP. APP.
FIFTH SEMESTER NOVEMBER 2017
CS 5405/CA 5405 DATA MINING
Date: 13-11-2017 Dept. No. Max. 100 Marks
Time: 09:00-12:00
PART A
Answer ALL the questions. (10X2=20 Marks)
1. Define: Data Mining.
2. What is scaling?
3. What is market bucket analysis
4. List any two constraint based association mining.
5. What is the difference between prediction and classification?
6. Define Bayes' theorem.
7. What are outliers?
8. What is a Data matrix?
9. How is Data mining used in Telecommunication Industry?
10. List any two applications of Data mining.
PART B
Answer ALL the questions. X 8=40 Marks)
11 a. Explain about the architecture of Data Mining system.
b. Explain Entropy-Based Discretization
12 a. Explain about Association mining to correlation analysis.
b. Explain about Constraint based mining.
13 a. Discuss the issues in classification and prediction.
b. Explain about Classifier Accuracy measures.
14 a. Explain the distance measures used in Clustering.
b. Describe about Outlier analysis.
15 a.How is a Data mining useful for Biological Data analysis? Explain.
b. Explain about the social impacts of Data mining.
2
PART C
Answer any TWO questions. X 20= 40 Marks)
16 a. Explain data preprocessing in detail.
b. Explain the algorithm for finding the frequent item sets using candidate generation.
17 a. Explain in detail about mining single dimensional rules.
b. Explain the hierarchical and agglomerative clustering techniques.
18 a. Explain the trends in data mining.
b. Explain the forms of data preprocessing.
LOYOLA COLLEGE (AUTONOMOUS), CHENNAI 600 034
B.Sc.,B.C.A. DEGREE EXAMINATION COMPUTER SCIENCE &COMP. APP.
FIFTH SEMESTER NOVEMBER 2017
CS 5405/CA 5405 DATA MINING
Date: 13-11-2017 Dept. No. Max. 100 Marks
Time: 09:00-12:00
PART A
Answer ALL the questions. (10X2=20 Marks)
1. Define: Data Mining.
2. What is scaling?
3. What is market bucket analysis
4. List any two constraint based association mining.
5. What is the difference between prediction and classification?
6. Define Bayes' theorem.
7. What are outliers?
8. What is a Data matrix?
9. How is Data mining used in Telecommunication Industry?
10. List any two applications of Data mining.
PART B
Answer ALL the questions. X 8=40 Marks)
11 a. Explain about the architecture of Data Mining system.
b. Explain Entropy-Based Discretization
12 a. Explain about Association mining to correlation analysis.
b. Explain about Constraint based mining.
13 a. Discuss the issues in classification and prediction.
b. Explain about Classifier Accuracy measures.
14 a. Explain the distance measures used in Clustering.
b. Describe about Outlier analysis.
15 a.How is a Data mining useful for Biological Data analysis? Explain.
b. Explain about the social impacts of Data mining.
2
PART C
Answer any TWO questions. X 20= 40 Marks)
16 a. Explain data preprocessing in detail.
b. Explain the algorithm for finding the frequent item sets using candidate generation.
17 a. Explain in detail about mining single dimensional rules.
b. Explain the hierarchical and agglomerative clustering techniques.
18 a. Explain the trends in data mining.
b. Explain the forms of data preprocessing.
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