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Implement Frequent Itemset Mining Program in Python

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Apriori Algorithm in Python

Introduction

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.

Prune Stage

Apriori Algorithm use Property1 to "Prune" infrequent superset

This part cat see in Apriori_prune function in Apriori.py

Join Stage

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)

Usege

python Apriori.py

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