Quiznetik
Data Mining | Set 4
1. The __________ is an expensive process in building an expert system.
A. analysis.
B. study.
C. design.
D. information collection.
Correct : D. information collection.
2. The full form of KDD is____________.
A. knowledge database.
B. knowledge discovery in database.
C. knowledge data house.
D. knowledge data definition.
Correct : C. knowledge data house.
3. Which of the following is not a open source data mining tool.
A. WEKA
B. R
C. RapidMiner
D. KnowledgeMiner
Correct : D. KnowledgeMiner
4. Removing duplicate records is a process called________.
A. recovery.
B. data cleaning.
C. data cleansing.
D. data pruning.
Correct : B. data cleaning.
5. The __________ contains information that gives users an easy-to-understand perspective of the information stored in the data warehouse.
A. business metadata.
B. technical metadata.
C. operational metadata.
D. financial metadata.
Correct : A. business metadata.
6. A/An ___________helps to integrate, maintain and view the contents of the data warehousing system.
A. business directory.
B. information directory.
C. data dictionary.
D. database.
Correct : B. information directory.
7. Discovery of cross-sales opportunities are called_________.
A. segmentation.
B. visualization.
C. correction.
D. association.
Correct : D. association.
8. Data marts that incorporate data mining tools to extract sets of data is called______.
A. independent data mart.
B. dependent data marts.
C. intra-entry data mart.
D. inter-entry data mart.
Correct : B. dependent data marts.
9. Which of the following problems bog down the development of data mining projects
A. Financial problem.
B. Lack of technical assistance.
C. Lack of long-term vision.
D. Legal and privacy restrictions.
Correct : C. Lack of long-term vision.
10. The ___________can generate programs itself, enabling it to carry out new tasks.
A. automated system.
B. decision making system.
C. self-learning system.
D. productivity system.
Correct : D. productivity system.
11. The power of self-learning system lies in__________.
A. cost.
B. speed.
C. accuracy.
D. simplicity.
Correct : C. accuracy.
12. The human brain consists primarily of nerve cells called__________.
A. dendrites.
B. neurons.
C. synapse.
D. perceptron.
Correct : B. neurons.
13. Which of the following is not a decision tree node?
A. Root node.
B. Internal node.
C. Leaf node.
D. predicted node.
Correct : D. predicted node.
14. _______ is the closeness of repeated measurements to one another.
A. Precision.
B. Bias.
C. Accuracy.
D. non-scientific.
Correct : A. Precision.
15. Which of the following matrix consist asymmetric data?
A. Sparse data matrix.
B. Indentity matrix.
C. Confusion matrix.
D. Cross matrix.
Correct : A. Sparse data matrix.
16. A representation of data objects as columns and attributes as rows is called_________.
A. matrix.
B. data matrix.
C. table.
D. file.
Correct : B. data matrix.
17. Which of the following is not a data mining attribute?
A. nominal.
B. ordinal.
C. interval.
D. multiple.
Correct : D. multiple.
18. Patterns of machine-language program are_________.
A. definitive theories.
B. hypothesis.
C. not-definitive theories.
D. quantitative.
Correct : B. hypothesis.
19. Nominal and ordinal attributes are collectively referred to as_________ attributes.
A. qualitative.
B. perfect.
C. consistent.
D. optimized.
Correct : A. qualitative.
20. A data set can often be viewed as a collection of ______.
A. data mart.
B. data.
C. data object.
D. template.
Correct : C. data object.
21. An important element in machine learning is ________.
A. flow.
B. knowledge.
C. observation.
D. language.
Correct : C. observation.
22. Which of the following is the data mining tool?
A. C.
B. Weka.
C. C++.
D. VB.
Correct : B. Weka.
23. ___________ is used for discrete target variable.
A. Nominal.
B. Classification.
C. Clustering.
D. Association.
Correct : B. Classification.
24. Data mining is an integral part of _________.
A. SE.
B. DBMS.
C. KDD.
D. OS.
Correct : C. KDD.