Font size
WorksheetsData Mining
Total questions: 15
Worksheet time: 11mins
Data mining should have been more appropriately named as
data dredging
knowledge mining from data
knowledge extraction
data/pattern analysis
data archaeology
Examples of time-related or sequence data are
historical records, stock exchange data, and time-series ,biological sequence data
video surveillance, sensor data
the design of buildings, system components, or integrated circuits
text, image, video, audio data
None of the above
What are the functions of Data Mining?
Prediction and characterization
Association and correctional analysis classification
Cluster analysis and Evolution analysis
All of the above
Which of the following is an essential process in which the intelligent methods are applied to extract data patterns?
Warehousing
Data Mining
Text Mining
Data Selection
The output of data characterization can be presented in various forms
pie charts
bar charts
curves and multidimensional tables
multidimensional data cubes
all of the above
A frequent itemset typically refers to
items bought in sequential manner
a set of items that often appear together
structural forms
none of the above
buys(X, “computer”) ⇒ buys(X, “software”) [support = 1%,confidence = 50%] is
multidimensional association rule
Correlation rule
single-dimensional association rule
All of the above
Identify the incorrect option among the following which is not involved in data mining.
Data Exploration
Knowledge Extraction
Data Transformation
Data Archeology
What does OLTP stand for?
Offline transaction processing
Online transaction processing
Outline traffic processing
None
State whether True or False: Data warehouse is generally updated in real-time.
True
False
Identify the options below that a data warehouse can include.
Online data
Flat files
Database table
All of the above
Classification is the process of finding
a model
function
data classes
concepts
Tree leaves in decision tree represent
a test on an attribute value
class distributions
outcome of the test
classes
An outlier analysis is otherwise called as
objective measures
taxonomy formation
anomaly mining
subjective measures
Cluster Analysis is known as
outlier analysis
taxonomy formation
anomaly mining
none of the above
