Question

Given transaction database, write the apriori algorithm for minimum support n for produce all . the frequncy sets up to a k itemset length. print(F[0], F[1]..... F[k])

Also, what are the conditions of the loop ?

Answer 1

Apriori Algorithm:

Apriori algorithm is used to find frequently used items set from the given database and to find the association rules over the given transaction database.

• Algorithm:

Step 1:

Scan the given transaction database as per the given list of items. (Minimum support will be given) and find support count for each item.

Step 2:

Compare minimum support with the support count of all the items. Remove all the items whose support count is less than given minimum support.

Step 3:

Find Support count for two items together. (For Ex. we have item X, Y, Z the in this step you will be finding support count for item XY, XZ, YZ.)

Step 4:

Again compare support count with minimum support and remove unwanted item like step no 2.

Step 5:

Repeat step no 1 and 2 for 3 items, 4 items etc,.. unless you don't get the frequently used itemset whose support count is equal to minimum count.

• The condition of the for loop:

I_k: Candidate Itemset of size k

L_k : Frequent itemset of size k

L₁ = {frequent items}; for ( k = 1; L_k != ; k++) do begin I_k+1 = candidates generated from frequesnt Itemset; for each database transaction, increment the count of all Items in I_k+1 that are contained in t L_k+1 = Items in I_k+1 with minimum support count end return L_k