CAJ | 학술논문

针对属性过多对于有效的数据挖掘很不利以及约简中差别矩阵的产生会占用较大存储空间的问题,提出了一种基于粗糙集和信息增益的属性约简改进算法.该算法首先采用信息增益技术对决策表属性进行相关分析,删除部分冗余属性,减小属性约简的复杂度,然后直接从决策表中提取出分明函数,求出属性约简.由于避免了分明矩阵的生成,因此该算法不仅节约了时间和空间,而且提高了效率.
침대속성과다대우유효적수거알굴흔불리이급약간중차별구진적산생회점용교대존저공간적문제,제출료일충기우조조집화신식증익적속성약간개진산법.해산법수선채용신식증익기술대결책표속성진행상관분석,산제부분용여속성,감소속성약간적복잡도,연후직접종결책표중제취출분명함수,구출속성약간.유우피면료분명구진적생성,인차해산법불부절약료시간화공간,이차제고료효솔.
Aiming at the problems of too many attributes in data mining and much space acquired while generating the discernibility matrix, an improved algorithm for attribute reduction which is based on the rough sets and information gain, is put forward. The analysis of information gain technology is used to analyze the relationship between attributes to reduce the complexity of reduction. We can get the attribute reduction without generating the discernibility matrix. Less time and space complexity are acquired. And it is verified that the algorithm is effective.