data mining

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CMP 627 Data MiningCMP 627 Data MiningWeek 3 Homework Assignment 11CMP 627 Data Mining1. A database has four transactions. Let min sup = 60% and min conf = 80%.CIDTID01T100Items Bought{Kings-Crab, Sunset-Milk, Dairyland-Cheese, Best-Bread }{Best-Cheese, Dairyland-Milk, Goldenfarm-Apple, Tasty-Pie, Wonder-02T200Bread}01T300{Westcoast-Apple, Dairyland-Milk, Wonder-Bread, Tasty-Pie}03T400{Wonder-Bread, Sunset-Milk, Dairyland-Cheese}(a) At the granularity of item category (e.g., itemi could be Milk), for the followingrule template,X transaction, buys(X, item1) buys(X, item2) buys(X, item3) [s, c]List the frequent k-itemset for the largest k, and all of the strong association rules(with their support s and confidence c) containing the frequent k-itemset for the largestk.(b) At the granularity of brand-item category (e.g., itemi could be Sunset-Milk), forthe following rule template,X customer, buys(X, item1) buys(X, item2) buys(X, item3)List the frequent k-itemset for the largest k (but do not print any rules).2CMP 627 Data MiningAns.a) k = 3. The frequent 3- itemset is {bread, milk, cheese}The rules are:Bread Cheese => Milk,[75%, 100%]Cheese Milk => Bread,[75%, 100%]Cheese => Milk Bread,[75%, 100%]b) k = 3 and the frequent 3-itemset is {(Wonder-Bread, Dairyland-Milk, Tasty-Pie),(Wonder-Bread, Sunset-Milk, Dairyland-Cheese)}.2. A database h

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