摘要
要从数据量庞大的大型数据库中发现知识 ,就不得不考虑学习算法的效率。将粗集理论应用到数据挖掘中 ,实现了从数据库中自动抽取与给定的学习任务相关的属性 ,能有效地发现简练、贴切的知识 。
Knowledge mining and discovery is a new technology for decision support system beginning in the middle of 1990s. This is a combination of artificial intelligence, machine learning and database technology. To mine knowledge from large databases, the efficiency of leaning algorithms has to be considered. Applying rough set theory to data mining, the attributes relevant to the mining task can be drawn from databases, and simultaneously simple and concise knowledge can be found effectively. The theoretical basis of this application and the realization of the algorithm are presented and discussed.
出处
《空军工程大学学报(自然科学版)》
CSCD
2004年第3期68-70,74,共4页
Journal of Air Force Engineering University(Natural Science Edition)
基金
山东省教育厅科技计划项目 (J0 2F0 6 )