基于相关数学模型的关联规则应用研究

An Investigation of Association Rules Based on Relation Mathematical Model

1 引言 数据挖掘[1]是一个从数据中提取出有效的、新颖的、潜在有用的、并能最终被人理解的模式的非平凡过程.数据挖掘可以挖掘出的知识包括关联规则(Association)、特征规则(Characterization)、分类规则(Classification)、聚类规则(Clustering)和趋势规则(Trend)等.数据挖掘是一交叉学科,涉及到诸如统计学、数据库、人工智能、数据可视化等学科.

The relation mathematical model is a method of analyzing spatial distribution features of reliant relations one another among every geographical factors- First,this paper analyzes population growth rate and GDP growth rate by providence in China in 90-92,92-94,94-96 and 96-98. In 90-92,the general trend is:population growth rate is descending; GDP growth rate is descending;the regions in which population growth is high are developed regions. The relation of population growth rate and GDP growth rate in defferent periods with relation mathematical model method is studied as well. According to most developed areas and some poor areas,population growth is in inverse proportion to GDP growth rate,while population growth is in proportion to GDP growth rate according to most medium developed areas and the other poor areas. All these results are according with real in China. So we can see that relation mathematical model is useful method in mining association rules.