M.Sc. DEGREE EXAMINATION, NOVEMBER/DECEMBER 2017.
Third Semester
Data Science
Paper V MACHINE LEARNING FOR BIG DATA
2 21435
Time 3 Hours Max. Marks 70
SECTION — A
Answer any FIVE questions. 6 30 Marks)
Each question carries 6 marks.
1. State and describe machine learning cycle.
2. Briefly explain the terms Data privacy and Data quality.
3. Explain about multilayer perceptron.
4. What is decision tree? Explain with suitable example.
5. Define the terms support, confidence, Lift and conviction of association rule
learning.
6. What is classification? Describe basic principles of classification.
7. Write about Hadoop architecture with neat sketch.
8. State and explain different applications of clustering.
SECTION — B
Answer ONE question from each Unit. 10 40 Marks)
Each question carries 10 marks.
UNIT I
9. Discuss about different cloud based services and various sources data storage.
Or
10. What is machine learning? What are the objectives of machine learning?

UNIT II
11. State the Baye's rule? How to construct Bayesian network for uncertainty
problems.
Or
12. Illustrate back propagation process with suitable example.
UNIT III
13. Explain about Apriori algorithm for association rule mining with example.
Or
14. Briefly explain about the following:
Support vector machines
Linear regression.
UNIT IV
15. Discuss various considerations for batch processing.
Or
16. Briefly explain about the features of following technologies:
Sqoop Pig Map — reduce
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