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problem 1: What is data mining? Describe the features and benefits of data mining in detail.

problem 2: Give the overview of statistical perspective on data mining.

problem 3: Describe in full detail the score function for descriptive models.

problem 4: What do you mean by SQL? What are the different ways of assessing a query?

problem 5: Describe about different partitional algorithms which are used for data clustering.

problem 6: Describe the procedure comprised in hypothesis testing.

problem 7: Describe in detail about the fuzzy sets and fuzzy logic.

problem 8: prepare the PAM algorithm for clustering.

problem 9: prepare brief notes on DBSCAN.

problem 10: Describe the EM algorithm for mining data.

problem 11: What is decision tree? Describe.

problem 12: prepare the fundamental algorithm for the association rules.

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  • Category:- DBMS
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