计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2009年
31期
115-117,124
,共4页
覆盖算法%Rough集理论%知识约简%条件信息熵
覆蓋算法%Rough集理論%知識約簡%條件信息熵
복개산법%Rough집이론%지식약간%조건신식적
covering algorithm%rough set theory%reduction conditional information entropy
利用覆盖算法对数据进行处理,得到论域U的一个划分,定义一种基于覆盖的条件信息熵,由新的条件信息熵定义新的属性重要性.并证明了对于一致决策表,它与代数定义下的重要性是等价的.以新的属性重要性为启发信息设计约简算法,并给出计算新的条件信息熵的算法.实验结果表明该约简算法能快速搜索到最优或次优约简.
利用覆蓋算法對數據進行處理,得到論域U的一箇劃分,定義一種基于覆蓋的條件信息熵,由新的條件信息熵定義新的屬性重要性.併證明瞭對于一緻決策錶,它與代數定義下的重要性是等價的.以新的屬性重要性為啟髮信息設計約簡算法,併給齣計算新的條件信息熵的算法.實驗結果錶明該約簡算法能快速搜索到最優或次優約簡.
이용복개산법대수거진행처리,득도론역U적일개화분,정의일충기우복개적조건신식적,유신적조건신식적정의신적속성중요성.병증명료대우일치결책표,타여대수정의하적중요성시등개적.이신적속성중요성위계발신식설계약간산법,병급출계산신적조건신식적적산법.실험결과표명해약간산법능쾌속수색도최우혹차우약간.
Processing data can be partitioned using covering algorithm.In this paper,a new concept of conditional information entropy is put forward, and then the new significance of an attributes is defined based on this entropy .In a consistent decision table,the equivalence between algebraic significance and conditional information entropy significance of attributes is proved.But it is incorrect in the inconsistent decision table.A heuristic algorithm for knowledge reduction is designed.The experimental results show that this algorithm can find the minimal or optimal reduction.
