Exam Details
| Subject | data mining and techniques | |
| Paper | ||
| Exam / Course | m.sc. information technology | |
| Department | ||
| Organization | acharya nagarjuna university-distance education | |
| Position | ||
| Exam Date | May, 2017 | |
| City, State | new delhi, new delhi |
Question Paper
Total No. of Questions 18] [Total No. of Pages 02
M.SC. DEGREE EXAMINATION, MAY 2017
(Second Year)
INFORMATION TECHNOLOGY
Data Mining and Techniques
Time 3 Hours Maximum Marks 70
SECTION-A × 15 45)
Answer any three questions
Q1) What is principal component analysis? Explain
Q2) Explain apriori algorithm for association rule mining?
Q3) Explain scoring models with different complexities?
Q4) Discuss the hierarchical clustering algorithm?
Q5) Explain index structures?
SECTION-B × 4 20)
Answer five from the following
Q6) What are the tools used displaying more than two variables? Explain?
Q7) Explain about statistical inference?
Q8) Explain pattern structures for strings?
Q9) Explain about systematic search and search heuristics?
Q10) Explain logistics discriminant analysis?
Q11) Explain artificial nueral networks?
Q12) Compare OLAP and OLTP?
Q13) Explain the generalized linear models?
SECTION-C × 1
Answer all questions
Q14) What is scatter plot matrix?
Q15) Define meta data?
Q16) Define optimization?
Q17) What is data ware house?
Q18) What is regression?
M.SC. DEGREE EXAMINATION, MAY 2017
(Second Year)
INFORMATION TECHNOLOGY
Data Mining and Techniques
Time 3 Hours Maximum Marks 70
SECTION-A × 15 45)
Answer any three questions
Q1) What is principal component analysis? Explain
Q2) Explain apriori algorithm for association rule mining?
Q3) Explain scoring models with different complexities?
Q4) Discuss the hierarchical clustering algorithm?
Q5) Explain index structures?
SECTION-B × 4 20)
Answer five from the following
Q6) What are the tools used displaying more than two variables? Explain?
Q7) Explain about statistical inference?
Q8) Explain pattern structures for strings?
Q9) Explain about systematic search and search heuristics?
Q10) Explain logistics discriminant analysis?
Q11) Explain artificial nueral networks?
Q12) Compare OLAP and OLTP?
Q13) Explain the generalized linear models?
SECTION-C × 1
Answer all questions
Q14) What is scatter plot matrix?
Q15) Define meta data?
Q16) Define optimization?
Q17) What is data ware house?
Q18) What is regression?
Subjects
- artificial intelligence
- basics of information technology
- computer networks
- computer organisation
- cryptography & network security
- data mining and techniques
- data structures with c
- database management systems
- operating systems
- programming with c++
- software engineering
- tcp / ip