Formal and Computational Properties of the Confidence Boost of Association Rules

03/24/2011
by   José L. Balcázar, et al.
0

Some existing notions of redundancy among association rules allow for a logical-style characterization and lead to irredundant bases of absolutely minimum size. One can push the intuition of redundancy further and find an intuitive notion of interest of an association rule, in terms of its "novelty" with respect to other rules. Namely: an irredundant rule is so because its confidence is higher than what the rest of the rules would suggest; then, one can ask: how much higher? We propose to measure such a sort of "novelty" through the confidence boost of a rule, which encompasses two previous similar notions (confidence width and rule blocking, of which the latter is closely related to the earlier measure "improvement"). Acting as a complement to confidence and support, the confidence boost helps to obtain small and crisp sets of mined association rules, and solves the well-known problem that, in certain cases, rules of negative correlation may pass the confidence bound. We analyze the properties of two versions of the notion of confidence boost, one of them a natural generalization of the other. We develop efficient algorithmics to filter rules according to their confidence boost, compare the concept to some similar notions in the bibliography, and describe the results of some experimentation employing the new notions on standard benchmark datasets. We describe an open-source association mining tool that embodies one of our variants of confidence boost in such a way that the data mining process does not require the user to select any value for any parameter.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/23/2010

Redundancy, Deduction Schemes, and Minimum-Size Bases for Association Rules

Association rules are among the most widely employed data analysis metho...
research
09/30/2018

Using Graph-Pattern Association Rules On Yago Knowledge Base

We propose the use of Graph-Pattern Association Rules (GPARs) on the Yag...
research
09/03/2019

Finding Maximal Non-Redundant Association Rules in Tennis Data

The concept of association rules is well–known in data mining. But often...
research
07/22/2019

Association rule mining and itemset-correlation based variants

Association rules express implication formed relations among attributes ...
research
03/06/2008

New probabilistic interest measures for association rules

Mining association rules is an important technique for discovering meani...
research
09/28/2017

SCARF: A Biomedical Association Rule Finding Webserver

The analysis of enormous datasets with missing data entries is a standar...
research
12/17/2021

Matching Social Issues to Technologies for Civic Tech by Association Rule Mining using Weighted Casual Confidence

More than 80 civic tech communities in Japan are developing information ...

Please sign up or login with your details

Forgot password? Click here to reset