First question is compulsory

Answer any FOUR from the remaining questions.

All questions carry equal marks.

Answer all parts of any questions at one place

1.Explain about the following

(a)Data cleaning

(b)Kneapsort neighbor classifier

(c)Regression

(d)Cluster analysis

2.(a)Write about the efficient computation of data cubes

(b)Explain about data processing

3. Explain about data warehousing architecture an its components with block diagram.

4.(a)How to implement attribute oriented induction technique?

(b)Explain the associate rule mining using market basket analysis.

5.(a)Explain statistical measures in large databases.

(b)Discuss about functional components of data mining GUI.

6.Write and explain Apriori algorithm.Implement it with an example.

7.(a)Com pare the advantages and disadvantages of eager classification versus lazy classification

(b)Explain decision tree induction with an example.

8.Explain how back propagation  is useful for classification of data.

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First question is compulsory Answer any FOUR from the remaining questions. All questions carry equal marks. Answer all parts of any questions at one place 1.Explain about the following (a)Data cleaning (b)Kneapsort neighbor classifier (c)Regression (d)Cluster analysis 2.(a)Write about the efficient computation of data cubes (b)Explain about data processing 3. Explain about data warehousing architecture an its components with block...