Finding Frequent Itemsets using Apriori and PCY algorithm.
This project is built with the motive of finding frequent items of size K(=1,2,3,..) from a large dataset using the Apriori algorithm.Apriori Algorithm enhances the processing speed of finding the frequent items because it works on the principle of montonocity.This is different from how a Naive Bayes algorithm would find frequent items. The running/processing time of this code is enhanced by a factor of ~10 % by deploying PCY algorithm which uses a bitmap in the second pass of going over the baskets.The PCY algorithm uses the spare main memory in the first pass which is not done in Apriori algorithm to store buckets and hash items to the buckets.