Data Mining MCQs Questions And Answers
This section focuses on "Data Mining" in Data Science. These Data Mining Multiple Choice Questions (MCQ) should be practiced to improve the skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations.
1. What is true about data mining?
A. Data Mining is defined as the procedure of extracting information from huge sets of data
B. Data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation
C. Data mining is the procedure of mining knowledge from data.
D. All of the above
View Answer
Ans : D
Explanation: Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. The information or knowledge extracted so that it can be used.
2. How many categories of functions involved in Data Mining?
A. 2
B. 3
C. 4
D. 5
View Answer
Ans : A
Explanation: there are two categories of functions involved in Data Mining : 1. Descriptive, 2. Classification and Prediction
3. The mapping or classification of a class with some predefined group or class is known as?
A. Data Characterization
B. Data Discrimination
C. Data Set
D. Data Sub Structure
View Answer
Ans : B
Explanation: Data Discrimination : It refers to the mapping or classification of a class with some predefined group or class
4. The analysis performed to uncover interesting statistical correlations between associated-attribute-value pairs is called?
A. Mining of Association
B. Mining of Clusters
C. Mining of Correlations
D. None of the above
View Answer
Ans : C
Explanation: Mining of Correlations : It is a kind of additional analysis performed to uncover interesting statistical correlations between associated-attribute-value pairs or between two item sets to analyze that if they have positive, negative or no effect on each other.
5. __________ may be defined as the data objects that do not comply with the general behavior or model of the data available.
A. Outlier Analysis
B. Evolution Analysis
C. Prediction
D. Classification
View Answer
Ans : A
Explanation: Outlier Analysis : Outliers may be defined as the data objects that do not comply with the general behavior or model of the data available.
6. "Efficiency and scalability of data mining algorithms" issues comes under?
A. Mining Methodology and User Interaction Issues
B. Performance Issues
C. Diverse Data Types Issues
D. None of the above
View Answer
Ans : B
Explanation: In order to effectively extract the information from huge amount of data in databases, data mining algorithm must be efficient and scalable.
7. To integrate heterogeneous databases, how many approaches are there in Data Warehousing?
A. 2
B. 3
C. 4
D. 5
View Answer
Ans : A
Explanation: Data warehousing involves data cleaning, data integration, and data consolidations. To integrate heterogeneous databases, we have the following two approaches : Query Driven Approach, Update Driven Approach
8. Which of the following is correct advantage of Update-Driven Approach in Data Warehousing?
A. This approach provides high performance.
B. The data can be copied, processed, integrated, annotated, summarized and restructured in the semantic data store in advance.
C. Both A and B
D. None Of the above
View Answer
Ans : C
Explanation: Both A and B are advantage of Update-Driven Approach in Data Warehousing.
9. What is the use of data cleaning?
A. to remove the noisy data
B. correct the inconsistencies in data
C. transformations to correct the wrong data.
D. All of the above
View Answer
Ans : D
Explanation: Data cleaning is a technique that is applied to remove the noisy data and correct the inconsistencies in data. Data cleaning involves transformations to correct the wrong data. Data cleaning is performed as a data preprocessing step while preparing the data for a data warehouse.
10. Data Mining System Classification consists of?
A. Database Technology
B. Machine Learning
C. Information Science
D. All of the above
View Answer
Ans : D
Explanation: A data mining system can be classified according to the following criteria : Database Technology, Statistics, Machine Learning, Information Science, Visualization, Other Disciplines
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