Data Mining Questions and Answers | DM | MCQ

 



The difference between supervised learning and unsupervised learning is given by
Select one:
a. unlike unsupervised learning, supervised learning can be used to detect outliers
b. unlike unsupervised learning, supervised learning needs labeled data –
c. unlike supervised leaning, unsupervised learning can form new classes
d. there is no difference
 
In asymmetric attribute
Select one:
a. All values are equals
b. Range of values is important
c. No value is considered important over other values
d. Only non-zero value is important –
 
Which of the following is not a Visualization Method?
Select one:
a. Hierarchical visualization technique
b. Tuple based visualization Technique –
c. Icon based visualization techniques
d. Pixel oriented visualization technique
 
Which of the following is NOT example of ordinal attributes?
Select one:
a. Ordered numbers
b. Military ranks
c. Movie ratings
d. Zip codes –
 
Which of the following activities is NOT a data mining task?
Select one:
a. Monitoring and predicting failures in a hydropower plant
b. Predicting the future stock price of a company using historical records
c. Extracting the frequencies of a sound wave –
d. Monitoring the heart rate of a patient for abnormalities
Which of the following data mining task is known as Market Basket Analysis?
Select one:
a. Association Analysis –
b. Outlier Analysis
c. Clasification
d. Regression
Which of the following is an Entity identification problem?
Select one:
a. One person with multiple phone numbers
b. Title for person
c. One person’s name written in different way –
d. One person with different email address
Which statement is not TRUE regarding a data mining task?
Select one:
a. Clustering is a descriptive data mining task
b. Deviation detection is a predictive data mining task
c. Classification is a predictive data mining task
d. Regression is a descriptive data mining task –
Dimensionality reduction reduces the data set size by removing _________
Select one:
a. derived attributes
b. irrelevant attributes –
c. relevant attributes
d. composite attributes
Which of the following statement is not TRUE for a Tag Cloud
Select one:
a. The importance of a tag is indicated by font size or color
b. Tag cloud is a visualization of statistics of user-generated tags
c. Tags may be listed alphabetically in a tag cloud
d. Tag cloud can be used for numeric data only –
The dissimilarity between two data objects is
Select one:
a. Applies only categorical attributes
b. Lower when objects are not alike
c. Higher when objects are more alike
d. Lower when objects are more alike –
Which of the following is NOT a data quality related issue?
Select one:
a. Duplicate records
b. Attribute value range –
c. Outlier records
d. Missing values
Which data mining task can be used for predicting wind velocities as a function of temperature, humidity, air pressure, etc.?
Select one:
a. Clasification
b. Cluster Analysis
c. Sequential pattern discovery
d. Regression –
The Data Sets are made up of
Select one:
a. Dimensions
b. Database
c. Attributes
d. Data Objects –



Which of the following is NOT an example of data quality related issue?
Select one:
a. Noise
b. Contradicting values
c. Using a field for different purposes
d. Multiple date formats –
Synonym for data mining is
Select one:
a. Data Warehouse
b. Knowledge discovery in database –
c. OLAP
d. Business intelligence
Which of the following is not a data pre-processing methods
Select one:
a. Data Discretization
b. Data Cleaning
c. Data Visualization –
d. Data Reduction
Identify the example of Nominal attribute
Select one:
a. Gender –
b. Salary
c. Temperature
d. Mass
In Binning, we first sort data and partition into (equal-frequency) bins and then which of the following is not a valid step
Select one:
a. smooth by bin means
b. smooth by bin median
c. smooth by bin boundaries
d. smooth by bin values –
Data set {brown, black, blue, green , red} is example of
Select one:
a. Continuous attribute
b. Ordinal attribute
c. Nominal attribute –
d. Numeric attribute