Boosting Frequent Itemset Mining via Early Stopping Intersections
Abstract
Mining frequent itemsets from a transaction database has emerged as a fundamental problem in data mining and committed itself as a building block for many pattern mining tasks. In this paper, we present a general technique to reduce support checking time in existing depth-first search generate-and-test schemes such as Eclat/dEclat and PrePost+. Our technique allows infrequent candidate itemsets to be detected early. The technique is based on an early-stopping criterion and is general enough to be applicable in many frequent itemset mining algorithms. We have applied the technique to two TID-list based schemes (Eclat/dEclat) and one N-list based scheme (PrePost+). Our technique has been tested over a variety of datasets and confirmed its effectiveness in runtime reduction.
Cite
@article{arxiv.1901.07773,
title = {Boosting Frequent Itemset Mining via Early Stopping Intersections},
author = {Huu Hiep Nguyen},
journal= {arXiv preprint arXiv:1901.07773},
year = {2019}
}