Data mining based on rough sets

Authors:
Jerzy W. Grzymala-Busse;Wojciech Ziarko
Affiliations:
University of Kansas;University of Regina, Canada
Venue:
Data mining
Year:
2003

Citing 20
Cited 13

Rough classification

International Journal of Man-Machine Studies
Induction: processes of inference, learning, and discovery

Induction: processes of inference, learning, and discovery
Machine learning an artificial intelligence approach volume II

Machine learning an artificial intelligence approach volume II
Classifier systems and genetic algorithms

Machine learning: paradigms and methods
Variable precision rough set model

Journal of Computer and System Sciences
Rough sets

Communications of the ACM
Rough sets, rough relations and rough functions

Fundamenta Informaticae - Special issue: rough sets
Variable precision extension of rough sets

Fundamenta Informaticae - Special issue: rough sets
A new version of the rule induction system LERS

Fundamenta Informaticae
Computer-based recognition of musical phrases using the rough-set approach

Information Sciences: an International Journal - From rough sets to soft computing
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems

Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Managing Uncertainty in Expert Systems

Managing Uncertainty in Expert Systems
Analysis of Self-Injurious Behavior by the LERS Data Mining System

Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence
A Machine Learning Experiment to Determine Part of Speech from Word-Endings

ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
ESEP: An Expert System for Environmental Protection

RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
A Closest Fit Approach to Missing Attribute VAlues in Preterm Birth Data

RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Decision Making with Probabilistic Decision Tables

RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Melanoma Prediction Using Data Mining System LERS

COMPSAC '01 Proceedings of the 25th International Computer Software and Applications Conference on Invigorating Software Development
Using Rule Induction for Prediction of Self-Injuring Behavior in Animal Models of Development Disabilities

CBMS '01 Proceedings of the Fourteenth IEEE Symposium on Computer-Based Medical Systems

A Comparison of the LERS Classification System and Rule Management in PRSM

RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Decision Rule Based Data Models Using NetTRS System Overview

Transactions on Rough Sets IX
An empirical comparison of rule sets induced by LERS and probabilistic rough classification

RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
On the relation between jumping emerging patterns and rough set theory with application to data classification

Transactions on rough sets XII
Data-driven adaptive selection of rules quality measures for improving the rules induction algorithm

RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Rough-set-inspired feature subset selection, classifier construction, and rule aggregation

RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Quality improvement of rule-based gene group descriptions using information about GO terms importance occurring in premises of determined rules

International Journal of Applied Mathematics and Computer Science
Decision rule-based data models using TRS and NetTRS – methods and algorithms

Transactions on Rough Sets XI
System health prognostic model using rough sets

RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Rule quality measure-based induction of unordered sets of regression rules

AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
Local probabilistic approximations for incomplete data

ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
CHIRA---Convex Hull Based Iterative Algorithm of Rules Aggregation

Fundamenta Informaticae
Redefinition of Decision Rules Based on the Importance of Elementary Conditions Evaluation

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

The chapter is focused on the data mining aspect of the applications of rough set theory. Consequently, the theoretical part is minimized to emphasize the practical application side of the rough set approach in the context of data analysis and model-building applications. Initially, the original rough set approach is presented and illustrated with detailed examples showing how data can be analyzed with this approach. The next section illustrates the Variable Precision Rough Set Model (VPRSM) to expose similarities and differences between these two approaches. Then, the data mining system LERS, based on a different generalization of the original rough set theory than VPRSM, is presented. Brief descriptions of algorithms are also cited. Finally, some applications of the LERS data mining system are listed.