【摘要】 属性约简是粗糙集理论研究的一个核心问题。为了有效地处理决策表中连续值属性约简,提出了连续值属性决策表中的可变精度粗糙集模型以及基于此模型的连续值属性约简算法。仿真实验结果表明,该算法可以对连续值属性进行约简,而且比经典粗糙集相关方法在处理连续值属性约简方面更有效。更多还原

【Abstract】 Attribute reduction is one of the key problems of the rough set theory.In order to effectively use the rough set theory to deal with the problem of attribute reduction in Decision Tables containing Continuous-Valued Attributes(DTCVA) directly,a new variable precision rough set model and a heuristic algorithm for attributes reduction in DTCVA were developed.Simulation results show that the proposed approach is effective for reduction of continuous-valued attributes,and more efficient than the classical rough set approaches in processing attribute reduction in decision information systems containing continuous-valued attributes.更多还原