Greedy Algorithms withWeights for Construction of Partial Association Rules

Authors:
Mikhail Ju. Moshkov;Marcin Piliszczu;Beata Zielosko
Affiliations:
(Correspd.) Division of Mathematical and Computer Sciences and Engineering, King Abdullah University of Science and Technology, P.O. Box 55455, Jeddah 21534, Saudi Arabia. mikhail.moshkov@kaust.ed ...;ING Bank Śląski S.A. 34, Sokolska St., Katowice 40-086, Poland. marcin.piliszczuk@ingbank.pl;Institute of Computer Science, University of Silesia 39, Bȩdzińska St., Sosnowiec 41-200, Poland. beata.zielosko@us.edu.pl
Venue:
Fundamenta Informaticae
Year:
2009

Citing 18
Cited 0

Mining quantitative association rules in large relational tables

SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A threshold of ln n for approximating set cover (preliminary version)

STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
A sub-constant error-probability low-degree test, and a sub-constant error-probability PCP characterization of NP

STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
&agr;-RST: a generalization of rough set theory

Information Sciences—Informatics and Computer Science: An International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Computational Complexity of Machine Learning

Computational Complexity of Machine Learning
Mining Optimized Association Rules with Categorical and Numeric Attributes

ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Discovery of Decision Rules by Matching New Objects Against Data Tables

RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Approximate Reducts and Association Rules - Correspondence and Complexity Results

RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Approximation algorithms for set cover and related problems

Approximation algorithms for set cover and related problems
Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications

Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications
Greedy Algorithm for Construction of Partial Association Rules

Fundamenta Informaticae
On partial covers, reducts and decision rules with weights

Transactions on rough sets VI
Approximate boolean reasoning: foundations and applications in data mining

Transactions on Rough Sets V
Approximate Entropy Reducts

Fundamenta Informaticae
Ensembles of Classifiers Based on Approximate Reducts

Fundamenta Informaticae - Concurrency Specification and Programming (CS&P'2000)
Normalized Decision Functions and Measures for Inconsistent Decision Tables Analysis

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper is devoted to the study of approximate algorithms for minimization of the total weight of attributes occurring in partial association rules. We consider mainly greedy algorithms with weights for construction of rules. The paper contains bounds on precision of these algorithms and bounds on the minimal weight of partial association rules based on an information obtained during the greedy algorithm run.