【摘要】 不完备信息系统中的知识获取是粗集理论应用的难点。通过引入信息熵和条件信息熵,对信息系统中属性的必要性进行了定义;提出了一种基于条件信息熵的知识约简启发式算法,并指出该算法的时间复杂度是多项式的。通过实例说明,该算法能得到信息表的约简和决策表的最小相对约简。更多还原

【Abstract】 Knowledge acquisition based on rough set theory is an important but difficult task under incomplete information systems. Information entropy and conditional information entropy are defined to express indispensable of attributes under incomplete information systems. A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed. Finally, an illustrative example analysis shows that this algorithm can find the minimal reduct for decision tables.更多还原