Question

A large supermarket tracks sales data by stock- keeping unit (SKU) for each item, such as “pasta”, “rice”, “egg”, “soup” is identified by a numerical SKU. The supermarket has a database of transactions where each transaction is a set of SKUs that were bought together. The database of transactions consist of following itemsets:

Transaction ID	Itemsets
T1	egg, soup
T2	rice, egg, soup
T3	rice, soup
T4	pasta, rice, egg, soup
T5	rice, egg
T6	pasta, rice, soup
T7	pasta, rice

Solve the above problem using Apriori Algorithm (Association Rule Mining) with minimum support of 3 and write each and every step.

Answer 1

Given transactions Transaction ID temoet T Tz T3 299, soup rice, egg, soup rice, soup Tч To pasta, rice, 099, soup rite, egg pasta, rre, soup pasta, rice step-1 kal create table for support count for the items in the dataset a itemset Sup-count 6 rice egs Soup 5 porta 3 Criven a mm. sunmort count of 3 we eleminate the row which are les than support-count. Since we have not found row which have led than the given support count of 3 any

- step2 k=2 Now, or generate candidate set C, wing L, The condition is Lk., and Lky is that is should have (K-2) elements in common. Sup Count 3 4 itenset rice, eggs voce, soups vice, parta egg, soup egg, pasta soup, pasta 3 3 1 2 Now generate C₂ and remove those items which are les than the mon.support count of 3. sup count itamset vile, egg vice, soup rice, pata e99, Soup 니 3 3 3 K 3 stop-3 generali Candidate set Ca osing L, that it show have (K-2) elements in common. itcomsel sup Count 2 rice, egg soup rice, soup, pasta 2

itemsets which have min sup count of 3. So we stop here geven min-sup here We have count 3 becawe no Pequent temsits found further. ave