A database has 5 transactions. Let min sup = 60% and min_conf = 80%. items.bought {M, O, N, K, E, Y} {D, O, N, K, E, Y} {M, А, К, Е} {M, U, C, К, Y} {С, О, О, К, І ,Е} TID T100 Т200 Т300 Т400 Т500 (a) Find all frequent itemsets using Apriori

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A database has 5 transactions. Let min_sup = 60% and min_conf = 80%.
items.bought
M, Ο , Ν, Κ , E , Y
{D, O, N, K, E, Y }
{М, A, К, Е}
{M, U, C, K, Y}
{С, О, О, К, І E}
TID
T100
T200
Т300
Т400
Т500
(a) Find all frequent itemsets using Apriori
(b) List all of the strong association rules (with support s and confidence c) matching the following
metarule, where X is a variable representing customers, and item; denotes variables representing
items (e.g., "A", "B", etc.):
Vx E transaction, buys(X, item1) A buys(X, item2) = buys(X, item3) [s, c]
Transcribed Image Text:A database has 5 transactions. Let min_sup = 60% and min_conf = 80%. items.bought M, Ο , Ν, Κ , E , Y {D, O, N, K, E, Y } {М, A, К, Е} {M, U, C, K, Y} {С, О, О, К, І E} TID T100 T200 Т300 Т400 Т500 (a) Find all frequent itemsets using Apriori (b) List all of the strong association rules (with support s and confidence c) matching the following metarule, where X is a variable representing customers, and item; denotes variables representing items (e.g., "A", "B", etc.): Vx E transaction, buys(X, item1) A buys(X, item2) = buys(X, item3) [s, c]
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