1)      What is analytical characterization? What is the need for attribute relevance analysis? briefly describe available method for attribute relevance analysis……….16

2)      Explain with an example data characterization and data discrimination.

3)      Describe in detail about the procedure for mining class comparisons.


How is class comparison performed?

4)      What is class comparison and how is it performed? With an example, using DMQL, briefly describe class comparison.

5)      With an example, describe in detail about data generalization, summarization and analytical characterization.

6)      How can we perform attribute relevance analysis for concept description? Explain.

7)      Briefly explain about the presentation of class comparison descriptions.

8)      Differentiate attribute generalization threshold control and generalized relation threshold control.

9)      Differentiate between predictive and descriptive data mining?

10)  Discuss why analytical characterization is needed and how it can be performed. Compare the result of two induction methods. I) with relevance analysis and 2) without relevance analysis.

11)  Explain attribute oriented induction


Write the algorithm for attribute oriented induction. Expalin the steps involved in it.

12)  Give an example of analytical characterization

13)  Discuss mining descriptive statistical measure in large databases.

14)   What is concept description? Explain presentation of the derived generalization.

15)  Explain efficient implementation of attribute oriented induction.

16)  What are the differences between concept description in large databases and OLAP?

17)  Write short notes for the following in detail:

a) Measuring the central tendency.

b) Measuring the dispersion of data.

      18) How can concept description mining be performed incrementally and in distributive       manner?

19) Explain about the graph displays of basic statistical class description.

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    March 2012