M.Sc. (Semester IV) (CBCS) Examination Nov/Dec-2018
Computer Science
DATA MINING AND WAREHOUSE
Time: 2½ Hours Max. Marks: 70
Instructions: Q.1 and Q.2 are compulsory.
Attempt any three questions from Q. 3 to 7.
Figures to the right indicate full marks.
Q.1 Choose the correct alternative: 14
Classification
A subdivision of a set of examples into a number of classes
A measure of the accuracy, of the classification of a concept that is
given by a certain theory
The task of assigning a classification to a set of examples
None of these
Which of the following is not a data mining functionality
Characterization and discrimination
Classification and regression
Selection and interpretation
Clustering and analysis
The data warehouse is
Read only Write only
Read write only None
The time horizon in data warehouse is usually
1-2 years 3-4 years
5-6 years 5-10 years
is a data transformation process
Comparison Projection
Selection Filtering
The terms equality and roll up are associated with
OLAP Visualization
Data mart Decision tree
Which of the following is the other name of data mining?
Exploratory data analysis Deductive learning
Data driven discovery All of the above
is the heart of the warehouse
Data mining database servers
Data warehouse database servers
Data mart database servers
Relational data base servers
is a subject-oriented, integrated, time variant, nonvolatile
collection of data in support of management decisions.
Data mining Data warehousing
Web mining Text mining
Page 2 of 2
SLR-VG-230
10) The star schema is composed of fact table
One Two
Three Four
State true or false
The term neural networks as used in data mining is a misnomer.
Data warehouse data are usually normalized.
Online analytical processing (OLAP) is a BI reporting system.
A data mart is a collection of data that while smaller than a data
warehouse, still addresses the entire business.
04
Q.2 Write Short notes of the following
Data mining primitives
Model based clustering methods.
08
Explain the following term
Classification and prediction
Neural network approach
06
Q.3 Answer the following
Why data mining is used? Explain what kinds of data can be mined? 07
Explain Discretization by decision tree and correlation analysis. 07
Q.4 Answer the following
Explain various OLAP operations in detail 07
What is meant by data warehouse? Explain data warehouse architecture in
detail.
07
Q.5 Answer the following
Explain star schema and snowflake schema in detail. 07
Explain issues and challenges in data mining. 07
Q.6 Answer the following
What is an association rule? Explain the methods to discover association
rules
07
What is meant by decision tree? Explain classification by back propagation. 07
Q.7 Answer the following
Explain data mining applications in detail. 07
Explain rule based classification algorithm. 07