Exam Details
| Subject | data mining | |
| Paper | ||
| Exam / Course | f.y. m.tech. (civil -structural engg.) | |
| Department | ||
| Organization | solapur university | |
| Position | ||
| Exam Date | 08, December, 2018 | |
| City, State | maharashtra, solapur |
Question Paper
F.Y. M.Tech.(Computer Science and Engineering) (Semester
(CBCS) Examination, 2018
data mining
Day and Date Saturday, 8-12-2018 Total Marks 70
Time 10.00 a.m. to 1.00 p.m.
Instructions Attempt any five questions from each Section.
Assume suitable data if needed.
Figures to the right indicate full marks.
SECTION I
1. Explain various components of data warehouse architecture. 7
2. Describe types of OLAP server. 7
3. List and discuss the issues in decision tree algorithms. 7
4. Explain in brief Bayesian Classification. 7
5. Explain in details Outliers in Data Mining. 7
6. Describe Apriori Algorithm and explain. 7
SECTION II
7. What is mining class comparison State and explain the procedure
for performance of class comparison. 7
8. Explain K-d tree trees with an example. 7
9. Explain Temporal Mining. 7
10. Explain web structure mining. 7
11. Write a short note on statistical data mining. 7
12. Explain in brief Spatial Clustering Algorithms. 7
(CBCS) Examination, 2018
data mining
Day and Date Saturday, 8-12-2018 Total Marks 70
Time 10.00 a.m. to 1.00 p.m.
Instructions Attempt any five questions from each Section.
Assume suitable data if needed.
Figures to the right indicate full marks.
SECTION I
1. Explain various components of data warehouse architecture. 7
2. Describe types of OLAP server. 7
3. List and discuss the issues in decision tree algorithms. 7
4. Explain in brief Bayesian Classification. 7
5. Explain in details Outliers in Data Mining. 7
6. Describe Apriori Algorithm and explain. 7
SECTION II
7. What is mining class comparison State and explain the procedure
for performance of class comparison. 7
8. Explain K-d tree trees with an example. 7
9. Explain Temporal Mining. 7
10. Explain web structure mining. 7
11. Write a short note on statistical data mining. 7
12. Explain in brief Spatial Clustering Algorithms. 7
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Subjects
- advanced design of concrete structures
- advanced design of foundation
- advanced digital signal processing
- advanced network system
- advanced solid mechanics (new)
- advanced structural analysis
- advanced vibrations and acoustics
- antena design and applications
- applied algorithms
- computational techniques in design enginering
- computer aided design (elective – i)
- data mining
- digital design and verification
- elective – 1 : advanced embedded system
- elective – i : analog and digital cmos vlsi design
- elective – i : biomedical signal processing
- elective – i : computer vision
- elective – i : image and video procesing
- elective – i : mechanical system design
- elective – i : natural language procesing
- elective – i : neural networks and fuzzy control systems
- elective – i : soft computing
- elective – i : wireles sensor networks
- industrial instrumentation
- machine learning
- object oriented software enginering (elective – i)
- reliability enginering (elective – i)
- research methodology and ipr
- soft computing methods
- structural dynamics
- theory of computation (new)
- voice and data networks