Application of bayesian confirmation measures for mining rules from support-confidence pareto-optimal set

Authors:
Roman Slowinski;Izabela Brzezinska;Salvatore Greco
Affiliations:
Institute of Computing Science Poznan University of Technology, Poznan, Poland;Institute of Computing Science Poznan University of Technology, Poznan, Poland;Faculty of Economics, University of Catania, Catania, Italy
Venue:
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 7
Cited 2

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization

SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data

SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Mining the most interesting rules

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Rule Induction with CN2: Some Recent Improvements

EWSL '91 Proceedings of the European Working Session on Machine Learning
Algorithms for Mining Association Rules for Binary Segmentations of Huge Categorical Databases

VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
On Classification and Regression

DS '98 Proceedings of the First International Conference on Discovery Science

Assessing the Quality of Rules with a New Monotonic Interestingness Measure Z

ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Analysis of symmetry properties for bayesian confirmation measures

RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

We investigate a monotone link between Bayesian confirmation measures and rule support and confidence. In particular, we prove that two confirmation measures enjoying some desirable properties are monotonically dependent on at least one of the classic dimensions being rule support and confidence. As the confidence measure is unable to identify and eliminate non-interesting rules, for which a premise does not confirm a conclusion, we propose to substitute the confidence for one of the considered confirmation measures. We also provide general conclusions for the monotone link between any confirmation measure enjoying some desirable properties and rule support and confidence.