B.C.A. (Semester (CBCS) Examination Nov/Dec-2018
DATA WAREHOUSE AND DATA MINING
Time: 2½ Hours Max. Marks: 70
Instructions: All questions are compulsory.
Figures to the right place indicate full marks.
Q.1 Choose correct alternatives: 14
Measure minimize the expected number of tests to classify a
given tuple.
Gini index Gain ratio
Information gain None
is used to day to day operations.
OLTP OLAP
OLAM None
is a summarization of the general characteristics or features of a
target class of data.
Data characterization Data Classification
Data discrimination Data selection
Outlier analysis is used on data objects which are than set of data.
Similar Dissimilar
Different None
The FP-growth algorithm has phase.
One Two
Three Four
Which of the following is the collection of data objects that are similar to one
another within the same group?
Partitioning Grid
Cluster Table
function is obtained by applying a distributive aggregate function.
Distributive Holistic
Algebraic None
The type of relationship in star schema
One to many Many to many
Many to one One to one
variable has only two states.
Interval scale Binary
Categorical Ordinal
10) rule involves associations between presence or absence of items.
Multilevel Correlation
Boolean Single level
11) The goal of is to discover both the dense and sparse regions of a
data set.
Association rule Classification
Clustering Genetic algorithm
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SLR-SH-26
12) The basic idea of the Apriori algorithm is to generate item sets of a
particular size scans the database.
Candidate Primary
Secondary Superkey
13) Which method of analysis does not classify variables as dependent or
independent?
Regression analysis Discrimination analysis
Analysis of variance Cluster analysis
14) The server is used to store and analyze highly volatile and changeable
data.
MOLAP ROLAP
HOLAP None
Q.2 Answer any Four of the following:- 08
What is data characterization?
What is correlation analysis for numeric data?
What is meant by clustering?
What is Bayesian Belief Networks?
What is meant by outlier detection?
Write notes on any two: 06
Explain difference between MOLAP and ROLAP.
Define and explain support and confidence.
Write short note on spatial data mining.
Q.3 Answer any two of the following: 08
Explain K-nearest-Neighbour classification.
Which are the various ways of classifying frequent pattern mining?
Apply all binning methods for the following sorted data with 3 bins.

Answer any one of the following: 06
What is concept hierarchies?
Normalize following data set by using min max normalization scale the
data in the range 0 and whereas v is
Dataset
Q.4 Answer any two of the following:- 10
Explain various applications of data mining.
Explain various attribute selection measures.
Explain maximal frequent itemset.
Answer any one of the following:- 04
Discus the Web mining.
Explain major tasks in data preprocessing.
Q.5 Answer any two of the following:- 14
Explain the various components of Data warehouse.
Explain different data types used in clustering.
A database has four transactions. Let min_sup 40% and min_conf 60%
find all frequent itemsets, using Apriori algorithm and find association rules.
TID Items bought
100
200
300
400