M.Sc. DEGREE EXAMINATION, NOVEMBER/DECEMBER 2017.
Third Semester
OR and SQC
DATA MINING
2 21234-A
Time 3 Hours Max. Marks 70
PART — A
Answer any FIVE questions. 6 30 Marks)
1. What is Data Mining? Describe major data repository systems.
2. What is data cleaning? Explain the approaches to data cleaning.
3. Explain the methods for concept hierarchy generation for categorical data.
4. Explain data cubes and their uses.
5. Explain the concepts of frequent pattern and frequent item sets.
6. Discuss the issues regarding classification and prediction.
7. Describe the types of data in cluster analysis.
8. What is an outlier? Explain a distance based outlier analysis.
PART — B
Answer ALL questions. 10 40 Marks)
9. Discuss descriptive data summarization techniques with suitable examples.
Or
Describe the data mining task primitives. Discuss the major issues in data
mining.

10. Discuss the strategies for data reduction.
Or
Describe the methods for efficient implementation of data warehouse
systems.
11. Discuss the methods for mining frequent item sets.
Or
Explain Decision tree induction and Bayesian classifiers with suitable
examples.
12. Explain partitioning and density based cluster methods.
Or
Explain hierarchical and grid based cluster methods.
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