The Algorithm of Mining Association Rules based on the Derivative of the Graph Model of the Datasets

被引：0

作者：

Valerievich, Bakulev Aleksandr ^{[1
]}

Alekseevna, Bakuleva Marina ^{[1
]}

机构：

[1] Ryazan State Radio Engn Univ RSREU, Ryazan, Russia

来源：

2018 7TH MEDITERRANEAN CONFERENCE ON EMBEDDED COMPUTING (MECO) | 2018年

关键词：

data mining; association rules; derivative of the modeling graph; weight of the derivative; confidence of the association rule; support association rule;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This article devote to mining association rules. We are given a large dataset from the database of hospital. Each transaction consists of health examination result of patients. We developed an efficient algorithm that generates association rules between items in the database. The algorithm based on the modeling graph (mograph) of analyzed set and differentiation one. We also present results of applying this algorithm which shows the effectiveness of the algorithm.

引用

页码：195 / 198

页数：4

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