Data Mining MCQ 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

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2. Which of the following is correct application of data mining?

A. Market Analysis and Management
B. Corporate Analysis & Risk Management
C. Fraud Detection
D. All of the above

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3. How many categories of functions involved in Data Mining?

A. 2
B. 3
C. 4
D. 5

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4. In Data Characterization, class under study is called as?

A. Study Class
B. Intial Class
C. Target Class
D. Final Class

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5. 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

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6. A sequence of patterns that occur frequently is known as?

A. Frequent Item Set
B. Frequent Subsequence
C. Frequent Sub Structure
D. All of the above

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7. 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

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8. __________ refers to the description and model regularities or trends for objects whose behavior changes over time.

A. Outlier Analysis
B. Evolution Analysis
C. Prediction
D. Classification

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9. __________ 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

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10. Pattern evaluation issue comes under?

A. Mining Methodology and User Interaction Issues
B. Performance Issues
C. Diverse Data Types Issues
D. None of the above

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11. "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

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12. "Handling of relational and complex types of data" issue comes under?

A. Mining Methodology and User Interaction Issues
B. Performance Issues
C. Diverse Data Types Issues
D. None of the above

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13. To integrate heterogeneous databases, how many approaches are there in Data Warehousing?

A. 2
B. 3
C. 4
D. 5

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14. Which of the following is correct disadvantage of Query-Driven Approach in Data Warehousing?

A. The Query Driven Approach needs complex integration and filtering processes.
B. It is very inefficient and very expensive for frequent queries.
C. This approach is expensive for queries that require aggregations.
D. All of the above

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15. 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

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16. The first steps involved in the knowledge discovery is?

A. Data Integration
B. Data Selection
C. Data Transformation
D. Data Cleaning

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17. 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

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18. In which step of Knowledge Discovery, multiple data sources are combined?

A. Data Cleaning
B. Data Integration
C. Data Selection
D. Data Transformation

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19. Data Mining System Classification consists of?

A. Database Technology
B. Machine Learning
C. Information Science
D. All of the above

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20. DMQL stands for?

A. Data Mining Query Language
B. Dataset Mining Query Language
C. DBMiner Query Language
D. Data Marts Query Language

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