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Data Mining - Part 1
1
of
25
Q1. DBSCAN has a drawback over OPTICS
A. fixed sized radiius
B. fixed sized points in radiius
C. core points
D. none of above
Q2. ___ often used for both the prelimi nary investigation of the data and the f inal data analysis
A. Aggregation
B. Feature creation
C. Sampling
D. Attribution transformation
Q3. The view over an operational data warehouse is known as virtual warehouse
A. TRUE
B. FALSE
Q4. k-means algorithm is sensitive to outliers
A. TRUE
B. FALSE
Q5. ___ refers to the grouping of records, observations, or cases into classes of similar objects
A. Clustering
B. Grouping
C. Classification
D. Gathering
Q6. Lift dari rule K ___ E adalah ___
×
A. 0.4
B. 0.6
C. 0.8
D. 1
Q7. Select the skills mainly required as a competent data analyst/scientist/miner
A. SQL
B. R
C. Java
D. All
Q8. Application server and data server are kept separately in.
A. Peer to Peer based Processing
B. Master slave based Processing
C. Host based Processing
D. 3-Tier Client Server model
Q9. ___ is the output of KDD
A. Query
B. Useful Information
C. Data
D. Information
Q10. This is a term that describes the large volume of data; both structured and unstructured.
A. Big Data
B. Big Knowledge
C. Big Information
D. Data at rest
Q11. Of the following which is not a distance based clustering algorithms?
A. K-Means
B. K-Medoids
C. BIRCH
D. DBSCAN
Q12. Select the tools that can be used for data mining
A. KNIME
B. WEKA
C. RATTLE
D. All
Q13. Find the median of these numbers:4,2,7,4,3
A. 2
B. 5
C. 7
D. 4
Q14. A collection of integrated, subject oriented databases designed to support the decision-support functions
A. Database
B. Data Collection
C. Data Warehouse
D. Data retrieval
Q15. Ordinal is an example of ___
A. Ratio class
B. Interval class
C. Categorical class
D. Range class
Q16. The mass of the beaker was 122 g.
A. Qualitative Data
B. Quantitative Data
Q17. a data warehouse can include
A. flat-files
B. database table
C. online data
D. all
Q18. In statistical distribution the outlier is identified using ___
A. working hypothesis
B. discontency test
C. alternative hypothesis
D. none of the above
Q19. Data mining is ___
A. A time variant non-Volatile collec tion of data
B. The actual discovery phase of a Knowledge
C. The stage of selecting the right data
D. None of these
Q20. ___ refers to the mapping or classifi cation of a class with some predefined group or class.
A. Data Discrimination
B. Data Characterization
C. Data Definition
D. Data Visualization
Q21. Of the following what are the distance based clustering algorithms?
A. K-Means
B. K-Medoids
C. Hierarchical
D. All
Q22. Suppose a cluster contain the points (1, 3), (3, 3), (2, 1). What is the centroid of the cluster?
A. (2, 2.33)
B. (2.33, 2)
C. (2, 3)
D. None
Q23. Which of the following is not involve in data mining
A. Data archaeology
B. Knowledge extraction
C. Data transformation
D. Data exploration
Q24. Is Logistic regression a supervised machine learning algorithm?
A. TRUE
B. FALSE
Q25. Same person with multiple email addresses is an example of ___
A. Noise
B. Outliers
C. Missing values
D. Duplicate data
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