关键词: 粗糙集, 属性约简, 属性重要度, 启发式算法

Abstract: Many data sets often vary dynamically in practical applications. Static attribute reduction algorithms consume a lot of time and space to solve these dynamical data sets. Since the data in set-valued decision information system are usually changed, a heuristic dynamic updating algorithm of attribute reduction is designed by introducing the concepts of conditional information quantity and significance of attribute. When new condition attributes are added to the set-valued decision information system, the proposed algorithm makes use of the attribute reduction results of the old system, updates the attribute reduction results quickly with the variation of attribute set, and deletes some redundant attributes in the new result of attribute reduction in reverse order, which keeps the knowledge concise and improves the computational efficiency. Finally, the effectiveness and feasibility of the proposed algorithm are validated by the examples.

Key words: rough sets, attribute reduction, significance of attribute, heuristic algorithm