It can only deal with discrete data . so continuous attributes must be discreted . researching the method of discretiz - ing attribute has important signification in theory and realistic . in this paper we have studied the methods of the discretization of continuous attributes and obtain knowledge from incomplete information systems 粗糙集的理论基础是集合论,它只能处理离散数据,现实中大量的实型数据必须进行离散化,因而,研究连续属性的离散化具有重要的理论和现实意义,本论文对连续属性离散化的方法及不完备信息系统的规则提取进行了研究。
实: solid型: mould; model数据: data; record; information型数据: attributes data大型数据库: large data base; large database典型数据: typical data定型数据集: training data set浮点型数据: floattype复型数据: complex data计量型数据: variables data逻辑型数据: logical data模型数据: model data; model information模型数据库: model database小型数据集: small data set小型数据库: toy database型数据时: datetime翼型数据: airfoil data整型数据: integer data实型: prototype; real type超大型数据库: very-large data base串型数据picture属性: picture attribute with string data; pictureattributewithstringdata大型数据处理: large data processing大型数据中心: large-scale data center非寿命型数据: non - lifetime data复制型数据库: replicated database