论文部分内容阅读
提出了一种新的基于粗糙集的概念模糊化决策树算法。本算法将利用属性归纳和概念模糊化的方法删除不能反映概化信息的属性,结合模糊粗糙决策树算法,提取对决策有潜在价值的知识和规则。
A new fuzzy decision tree algorithm based on rough set theory is proposed. This algorithm will remove the attributes that can not reflect the generalized information by using attribute induction and concept fuzzification, and combine the fuzzy rough decision tree algorithm to extract the knowledge and rules that have the potential value to the decision.