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Consider the following database containing five transactions. Let min_sup = 60%. Mine all frequent itemsets using Apriori and FP-growth algorithm. Compare the efficiency of the two mining processes.
TID
Transaction
T1
a, c, d, f, g, i, m, p
T2
a, b, c, f, l, m, o
T3
b, f, h, j, o
T4
b, c, k, p, s
T5
a, c, e, f, l, m, n, p
1. Staff (staffID --> availabilityID) 2. Services (servicesID --> itemBasedID --> timedBasedID) 3. TimedBased (timedbasedID--> priceid) 4. Clients (clientId, serviceId-->
Increased overheads on update : On the drawbacks side, it will need the system to ensure that all replicas of a relation are consistent. This shows that all the replicas of the rel
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Eliminate Columns Not Dependent On Key The Employee Relation satisfies - First normal form - As it has no repeating groups. Second normal form - As it do not have multi-a
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Extend your CREATE TABLE statement from problem 3 with referential integrity constraints. Updates and deletes on related rows are restricted. 6. From examination of the sample data
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