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.