RESUMEN
Rough set theory is a powerful tool to deal with incomplete information system, which can be applied to prescription data analysis. In this paper, we suggested an improved rough set model called WVP-T model. The model combined the variable precision model with the tolerance relation model. It can overcome the shortcoming of classical model. Furthermore, attribute importance and entropy of information were combined as heuristic information. Medicine was mapped to rough set attribute in order to value its importance. Then, combined with curative effect, attribute reduction was used to investigate the relationship between prescription and medicine and the relationship between symptom and syndrome. The experimental results showed that algorithm proposed in this paper can be used in prescription data analysis and can accurately reveal the compatibility rules to guide the clinical medication.