An Application for Knowledge Discovery Based on a Revision of VPRS Model

Authors:
Juan F. Gálvez;Fernando Diaz;Pilar Carrión;Angel Garcia
Affiliations:
-;-;-;-
Venue:
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Year:
2000

Citing 2
Cited 2

Variable precision rough set model

Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data

Rough Sets: Theoretical Aspects of Reasoning about Data

Rough sets for spam filtering: Selecting appropriate decision rules for boundary e-mail classification

Applied Soft Computing
Knowledge Bases Over Algebraic Models: Some Notes About Informational Equivalence

International Journal of Knowledge Management

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Abstract

In this paper, we present a particular study of the negative factors that affect the performance of university students. The analysis is carried out using the CAI (Conjuntos Aproximados con Incertidumbre) model that is a new revision of the VPRS (Variable Precision Rough Set) model. The major contribution of the CAI model is the approximate equality among knowledge bases. This concept joined with the revision of the process of knowledge reduction (concerning both attributes and categories), allow a significant reduction in the number of generated rules and the number or attributes per rule as it is showed in the case of study.