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Data Mining - Part 4
1
of
25
💡
Hints:
3
Q1. Using the table shown, calculate the value of the first point of the 3 point moving average.
×
A. 2
B. 3
C. 1.5
D. 2.5
Q2. Match the following:Divisive approach
A. Centeroid based technique
B. Top-down approach
C. Bottom- up approach
D. Representative object-based technique
Q3. Data can be stored,retrieved and update in
A. SMTOP
B. FTP
C. OLTP
D. OLAP
Q4. Given the following Confusion matrix. What is the Accuracy of the classifier?
×
A. 69.27%
B. 30.70%
C. 55.55%
D. 24.20%
Q5. DSS stands for ___
A. Deciding Support System
B. Decision Support System
C. Decision Software System.
Q6. Which of the following is not a Gridbased clustering
A. STING
B. WAVECLUSTER
C. DENCLUE
D. ALL OF THE ABOVE
Q7. The amount of data being generated, and in the age of big data, more data is being generated every minute than ever before
A. Variety
B. Veracity
C. Velocity
D. Volume
Q8. Discrete or continuous data?
×
A. Discrete
B. Continuous
Q9. "Efficiency and scalability of data mining algorithms" issues comes under?
A. Performance Issues
B. Diverse Data Types Issues
C. Mining Methodology and User Interaction Issues
D. None of the above
Q10. Joe is losing an average of .5 pounds a week. Is this continuous or discrete data?
A. Discrete
B. Continuous
Q11. Choose which data mining task is the most suitable for the following scenario: Predict fraudulent cases in credit card transactions
A. Classification
B. Association rules
C. Anomaly detection
D. A and C
Q12. What is discretization ___
A. dividing the given data in equal width
B. dividing the data with repective content
C. spliting up of data
D. conversion of data
Q13. Redundancy refers to the elements of a message that can be derived from other parts of ___
A. same message.
B. different message
C. irrelevant message.
Q14. Similar meaning to data mining
A. knowledge extraction
B. data/pattern analysis
C. data archaeology
D. All the above
Q15. Bioinformatics applies the techniques of ___ to address problems inspired by biology EXCEPT
A. computer science
B. statistics
C. engineering
D. applied mathematics
Q16. True or False:Data Mining can turn large collection of data into knowledge.
A. TRUE
B. FALSE
Q17. The issues like efficiency, scalability of data mining algorithms comes under
A. Performance issues
B. Diverse data type issues
C. Mining methodology and user interaction
D. All of the above
Q18. Before choosing an algorithm, I should define the :(2 answers)
A. field
B. need
C. approach
D. risk
Q19. Knowledge discovery in database refers to ___
A. whole process of extraction of knowledge from data
B. selection of data
C. coding
Q20. Foreign key constraints are also referred as
A. consistency constraints.
B. referential integrity.
C. conditional integrity.
D. domain constraints.
Q21. These refers to a problem that continues to plague data analysis methods.
A. Variable data
B. Missing data
C. Complete data
D. Field data
Q22. What is data?
A. Collection of attributes defined by objects.
B. Collection of objects defined by informations.
C. Collection of informations defined by objects.
D. Collection of objects defined by attributes.
Q23. Python was invented by whom and when?
A. Guido van, 1991
B. Rossum, 1990
C. Robert Rossum,1995
D. JIM kenery , 1994
Q24. The number of suitcases lost by airlines.
A. Discrete
B. Continuous
Q25. Which of the following is not the task of data preprocessing
A. Data Cleaning
B. Data Integration
C. Data Transformation
D. Pattern Mining
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