医学数据通常属性较多,这在很大程度上限制了信息系统对医疗数据的挖掘效率。通过分析粗糙集正域的相关思想,结合医学领域数据的特点,提出一种基于粗糙集正域的医疗决策表约简算法,并将其应用在医学诊断中。通过实例验证了该算法在医疗决策表约简中的正确性和有效性,具有一定的实用价值。
Usually Medical data has a long list of attributes, which badly affected the efficiency of the existing medical data mining systems. Based on the analysis of the positive region of the rough set and the characteristics of medical data, this thesis proposes a reduction algorithm based on rough set positive region, which is used for medical decision table reduction and medical diagnosis. Examples verify the correctness and validity of this algorithm in medical decision table reduction and the practical value of the algorithm.