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The motivation of the project is to identify the legislators who voted frequently against their party in terms of their roll call votes using Office of Clerk U.S. House of Representatives Data Sets collected in 2018 and 2019. We construct a model to predict the parties of legislators based on their votes. The method we used is Decision Tree from Data Mining. Python was used to collect raw data from internet, SAS was used to clean data, and all other calculations and graphical presentations are performed using the R software.


This poster, first place winner for non-STEM individual projects, was presented at the 32nd Semi-Annual Honors and Undergraduate Research Scholars Poster Presentation at New York City College of Technology, May 11, 2020. Mentor: Professor Nan Li (Mathematics).