This is old mining algorithm in mining Association Rules

And I implement this Algorithm from this paper

R. Agrawal and R. Srikant. “Fast Algorithms for Mining Association Rules.” Proc. 1994 Int’l Conf. Very Large Data Bases (VLDB ’94), pp. 487-499, Sept. 1994 .io

There are two property in Frequent Itemset Mining

Property1: if an itemset is infrequent, all it supersets must be infrequent and they need not be examined futher.

Property2: if an itemset is frequent, all its subsets must be frequent and they need not be examined further.

Apriori Algorithm use Property1 to "Prune" infrequent superset

This part cat see in Apriori_prune function in Apriori.py

Apriori Algorithm use Apriori_gen to create k+1 candidate

Combines two frequent k-itemset(now k=3),which have same k-1 prefix to generate new (k+1)-itemsets

Example:

k=3 Ck=(a,b,c),(a,b,e) 

Have same k-1 prefix (a,b) 

Can combine generate (k+1)-itemset(k=4)  

Ck+1=(a,b,c,e)

python Apriori.py