Data Mining Multiple Choice Questions and Answers for Practice

16. Which one is an example for case based-learning.

1. Decision trees.
2. Neural networks.
3. Genetic algorithm.
4. K-nearest neighbor.

17. Redundancy refers to the elements of a message that can be derived from other parts of

1. different message.
2. irrelevant message.
3. same message.
4. complete message.

18. Data mining algorithms require

1. efficient sampling method.
2. storage of intermediate results.
3. capacity to handle large amounts of data.
4. All of the above.

19. The next stage to data selection in KDD process

1. enrichment.
2. coding.
3. cleaning.
4. reporting.

20. What is the first stage in genetic algorithm.

1. Evaluation of each string.
2. Selection of string.
3. Creation of population of string.
4. Genetic manipulation.

21. EIS stands for

1. Executive Information System.
2. Exchange of Information System.
3. Extra Information System.
4. Extended Information system.

22. A coding operation in which an attribute with cardinality n is replaced by n binary attributes is called as

1. falsification of table.
2. enrichment of table.
3. flattening of table.
4. fuzzification of table.

23. What is one of the genetic operators that are used to recombine the population of genetic material.

1. genetic operator.
2. mutation operator.
3. cross over operator.
4. encoding operator.

24. A database containing volatile data used for daily operation of an organization is

1. historic data.
2. metadata.
3. knowledge.
4. operational data.

25. The technique of learning by generalizing from examples is

1. incremental learning.
2. inductive learning.
3. hybrid learning.
4. generalized learning.

26. Genetic algorithm was proposed by

1. John Holland.
2. Johnson.
3. Watson.
4. Kohenon.

27. Which is the technique which is used for discovering patterns in dataset at the beginning of data mining process.

1. Kohenon map.
2. Visualization.
3. OLAP.
4. SQL.

28. A natural way to visualize the process of training a self-organizing map is called

1. kohonen movie.
2. kohonen map.
3. frame.
4. scatter diagram.

29. K-nearest neighbor is one of the

1. learning technique.
2. OLAP tool.
3. purest search technique.
4. data warehousing tool.

30. The complexity of data mining algorithm is represented by

1. log n.
2. 2n log n.
3. n log n.
4. 2 log n.