Data mining techniques to study voting patterns in the US

Data Science Journal

Dustin Mink¹  Patrick Cash¹  Sikha Bagui¹ 

[1] Department of Computer Science, University of West Florida

关键词: Data mining;    Data preprocessing;    Attribute relevance study;    Association rule mining;    Decision tree analysis;    Voting patterns;   

DOI  :  10.2481/dsj.6.46

学科分类：计算机科学（综合）

来源: Ubiquity Press Ltd.

【 摘 要 】

References(19)This paper presents data mining techniques that can be used to study voting patterns in the United States House of Representatives and shows how the results can be interpreted. We processed the raw data available at http://clerk.house.gov, performed t-weight calculations, an attribute relevance study, association rule mining, and decision tree analysis and present and interpret interesting results. WEKA and SQL Server 2005 were used for mining association rules and decision tree analysis.

【 授权许可】

Unknown