Master of Science II (Computer Science)
Examination: Oct Nov 2016 Semester -IV (New CGPA)
SLR No. Day
Date Time Subject Name Paper No. Seat No.
SLR SC
325
Saturday
19/11/2016
2:30 P.M
to
5:00 P.M
Data Mining and
Warehouse
C
XIV
Instructions: Q.No.1 and 2 are compulsory.
Answer any three questions from Q.No.3 to Q.No.7.
Figures to the right indicates full marks.
Q.1 Choose the correct alternative: 10
The data Warehouse is
read only write only
read write only none
The star schema is composed of fact table.
Three two
one four
data are noisy and have many missing attribute values.
Preprocessed Cleaned
Transformed Real world.
Data mining is
The actual discovery phase of a knowledge discovery process.
The stage of selecting the right data for KDD process.
A subject oriented, integrated, time variant, nonvolatile collection
of data in support of management decisions.
None of these.
OLAP is oriented.
Business market
Management Customer
The 0 D cuboid, which holds the highest level of summarization is
called
Apex cuboid Base cuboid
3 D cuboid 2 D cuboid
The roll-up operation is also called the
Slicing drilling
drill-down drill-up
this refers to the ability to construct the classifier or
predictor efficiently given large amount of data.
Interpretability Scalability
Robustness None of these
Page 1 of 2
where encoding mechanism are used to reduce the data
set size.
Dimensionality
reduction
Attribute subset selection
Data cube aggregation Numerosity reduction
10) Cluster is
Group of similar objects that significantly from other objects
Operations of databases to transform or simplify data in order to
prepare it for a machine learning algorithm.
symbolic representation of facts or ideas from which information
can potentially be extracted.
None of these
State whether following statements are True or False:
An OLTP system mainly focuses on the historical data.
Hierarchical method can be classified as being either agglomerative or
divisive.
The Slice operation performs a selection on multiple dimensions.
Data cleaning which detects errors in the data and rectifies them when
possible.
Q.2 Write a short note on following. 08
Data Reduction
Visual and Audio Data Mining
Attempt the following questions: 06
Explain in short Data Warehouse Back-End Tools and utilities.
Explain Enterprise Warehouse.
Q.3 Answer the following: 14
Explain various OLAP operations with example.
What is data cube? Explain Star schema and Fact constellation schema
with diagram.
Q.4 Answer the following 14
Explain the decision tree induction algorithm.
Explain Rule Based classification.
Q.5 Answer the following: 14
What is Association Rule? Explain Apriori Algorithm with example.
Explain four major types of concept hierarchies.
Q.6 Answer the following: 14
Explain the procedure of K means Algorithm.
How Market basket analysis is useful in day to day life? Discuss in detail.
Q.7 Answer the following: 14
What is Cluster Analysis? Explain Agglomerative and Divisive
hierarchical clustering.
Explain various data mining applications in detail.