摘要
当数据的维数增加后,经典粗糙集分类方法将难以使用.本文针对经典的分类规则获取方法,在应用于高维的数据时,重要度计算所出现的问题,提出了改进方法,计算出了各个条件属性的重要度.然后根据获得的重要度,针对冠心病数据维数很高的特点,提出了新的分类规则获取方法.将这一思路应用于具体数据后,推导出了最终的分类规则,达到了准确的分类冠心病数据的最终目的.
When the dimension of data is increased, it is difficult to use the classical rough set. Being dead against the question of importance calculation on the high dimension data, the paper brings forward a new method. It calculates the importance of every qualification attribute first, and then presenta new classification rule acquire new method for the high dimension coronary heart disease data based on the gotten importance. After the idea is applied on real data, the final classification rules are deducted, and the final goal of the exact classification of coronary heart disease data is reached.
出处
《天津理工大学学报》
2007年第1期70-73,共4页
Journal of Tianjin University of Technology
基金
天津市高等学校科技发展基金(20030621)
关键词
粗糙集
重要度
下近似集
属性
属性约简
规则获取
rough set
importance
low approximation
attribute reduction
rule generation