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.
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Gálvez, J.F., Diaz, F., Carrión, P., Garcia, A. (2001). An Application for Knowledge Discovery Based on a Revision of VPRS Model. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_36
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DOI: https://doi.org/10.1007/3-540-45554-X_36
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