MCQ on Data Mining with Answers set-1

This set of multiple-choice questions – MCQ on data mining includes collections of MCQ questions on the fundamentals of data mining techniques. It includes objective questions on the application of data mining, data mining functionality, the strategic value of data mining, and the data mining methodologies.

1. …………………. is an essential process where intelligent methods are applied to extract data patterns.
A) Data warehousing
B) Data mining
C) Text mining
D) Data selection

2. Data mining can also applied to other forms such as …………….
i) Data streams
ii) Sequence data
iii) Networked data
iv) Text data
v) Spatial data

A) i, ii, iii and v only
B) ii, iii, iv and v only
C) i, iii, iv and v only
D) All i, ii, iii, iv and v

3. Which of the following is not a data mining functionality?
A) Characterization and Discrimination
B) Classification and regression
C) Selection and interpretation
D) Clustering and Analysis

4. ……………………….. is a summarization of the general characteristics or features of a target class of data.
A) Data Characterization
B) Data Classification
C) Data discrimination
D) Data selection

5. ……………………….. is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes.
A) Data Characterization
B) Data Classification
C) Data discrimination
D) Data selection

6. Strategic value of data mining is ………………….
A) cost-sensitive
B) work-sensitive
C) time-sensitive
D) technical-sensitive

Read Also: MCQ Questions on Data Warehouse

7. ……………………….. is the process of finding a model that describes and distinguishes data classes or concepts.
A) Data Characterization
B) Data Classification
C) Data discrimination
D) Data selection

8. The various aspects of data mining methodologies is/are ……………….
i) Mining various and new kinds of knowledge
ii) Mining knowledge in multidimensional space
iii) Pattern evaluation and pattern or constraint-guided mining.
iv) Handling uncertainty, noise, or incompleteness of data
A) i, ii and iv only
B) ii, iii and iv only
C) i, ii and iii only
D) All i, ii, iii and iv

9. The full form of KDD is ………………
A) Knowledge Database
B) Knowledge Discovery Database
C) Knowledge Data House
D) Knowledge Data Definition

10. The output of KDD is ………….
A) Data
B) Information
C) Query
D) Useful information

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Answers:

1. …………………. is an essential process where intelligent methods are applied to extract data patterns.
B) Data mining

2. Data mining can also be applied to other forms such as …………….
i) Data streams
ii) Sequence data
iii) Networked data
iv) Text data
v) Spatial data
D) All i, ii, iii, iv and v

3. Which of the following is not a data mining functionality?
C) Selection and interpretation

4. ……………………….. is a summarization of the general characteristics or features of a target class of data.
A) Data Characterization

5. ……………………….. is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes.
C) Data discrimination

6. Strategic value of data mining is ………………….
C) time-sensitive

7. ……………………….. is the process of finding a model that describes and distinguishes data classes or concepts.
B) Data Classification

8. The various aspects of data mining methodologies is/are ……………….
i) Mining various and new kinds of knowledge
ii) Mining knowledge in multidimensional space
iii) Pattern evaluation and pattern or constraint-guided mining.
iv) Handling uncertainty, noise, or incompleteness of data
D) All i, ii, iii and iv

9. The full form of KDD is ………………
B) Knowledge Discovery Database

10. The output of KDD is ………….
D) Useful information

Read Next: MCQ on Data Warehouse with Answers set-2