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Data Mining - Part 2
1
of
25
💡
Hints:
3
Q1. Which of the following statement is true about classification?
A. It is a measure of accuracy
B. It is a subdivision of a set
C. It is the task of assigning a classification
D. None of the above
Q2. ___ 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
Q3. There are 13 boys and 14 girls in fifth period.
A. Qualitative Data
B. Quantitative Data
Q4. To identify the truly interesting patterns representing knowledge based on interestingness measures is
A. Data transformation
B. Data selection
C. Pattern evaluation
D. Knowledge presentation
Q5. Which of the following statement about DBSCAN algorithm is false?
A. Can find arbitrarily shaped clusters
B. No need to specify number of clusters
C. Robust to outliers
D. Not sensitive to parameters
Q6. ___ stores sequences of values or events obtained over repeated measurements of time.
A. temporal database
B. sequence database
C. ime series database
D. all of the above
Q7. If during data mining, some data is incomplete, the team should seeking out the incomplete data
A. TRUE
B. FALSE
Q8. OLAP processing referred as
A. online analytical processing
B. online transaction processing
C. online information processing
D. online data processing
Q9. k-means is more Robust than k-medoids
A. TRUE
B. FALSE
Q10. Which of the following is NOT one of the processes in Data Preprocessing?
A. Feature creation
B. Sampling
C. Discriminization
D. Aggregation
Q11. Of the following what are the Density based clustering algorithms?
A. DBSCAN
B. OPTICS
C. BIRCH
D. CURE
Q12. Which of the following technique is categorised as unsupervised learning?
A. Decision Tree
B. Clustering
C. None of the above
Q13. Identifying the examples of sequence data
A. Datamatrix
B. Weather forecast
C. Market basket data
D. Genomic data
Q14. STING Stands for ___
A. Statistical Information Grid
B. Statistical Information Gain
C. Statistical information Genuie
D. none of the above
Q15. Data mining is a tool for allowing users to find the hidden relationships in data.
A. TRUE
B. FALSE
Q16. Example of a simple deployment phase in CRISP-DM
A. Generate a Output
B. Generate a form
C. Generate a report
D. None
Q17. What techniques can be used to improve the efficiency of apriori algorithm?
A. Hash-based techniques
B. Transaction Reduction
C. Partitioning
D. All of the above
Q18. Apply decision tree analysis using ___ node on a read world data set
A. IBM
B. IBM/SPSS
C. SPSS
D. IBM/SP
Q19. ___ is not a data mining functionality?
A. Clustering and Analysis
B. Selection and interpretations
C. Classification and regression
D. Characteristic and discriminators
Q20. Linear regression can be used to evalate trends and make forecasts e.g. on upward or downward trend in sales depicted as a result of linear analysis.
A. TRUE
B. FALSE
Q21. Discrete or continuous data?
×
A. Discrete
B. Continuous
Q22. The complexity of data mining algorithm is represented by ___
A. log n.
B. 2n log n.
C. n log n
Q23. Life Depends on Three Molecules
A. DNAs, RNAs, and Chromosomes
B. DNAs, Proteins, and Hormones
C. DNAs, RNAs, and Proteins
D. DNAs, RNAs, and Hormones
Q24. Given the following confusuin matrix for a multi class classifier. What is the accuracy of the classifier?
×
A. 0.72
B. 0.38
C. 0.9
D. 0.99
Q25. The technique of learning by generalizing from examples is ___
A. incremental learning.
B. inductive learning
C. hybrid learning
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