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Rochester Institute of Technology

1. Young, Jessica. Predicting Cholera Positive Cases in Haiti.

Degree: MS, School of Mathematical Sciences (COS), 2017, Rochester Institute of Technology

While Western countries typically run census surveys frequently, poorer countries such as Haiti do not have the money to do so; thus research into how Haitians live is severely lacking. Furthermore, studies that do exist tend to be not only old and outdated, but also lacking in depth. Using new census data recently collected from Haiti, I attempt to predict if certain behaviors and living situations can be used as indicators for determining if someone has cholera. Challenges for exploring this data center on getting the surveys into a format suitable for analysis and the severe class imbalance between the number of cholera positive people and cholera negative people. Numerous solutions to this problem are attempted including using different sampling techniques, using ensembles with models like CART and SVM, and Bayesian model averaging. Better survey designs and questions to add to future surveys are also discussed. Advisors/Committee Members: Ernest Fokoue, Steven Lalonde, Joseph Voelkel.

Subjects/Keywords: CART; Imbalanced data; R; Random forest; Survey design; SVM

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Young, J. (2017). Predicting Cholera Positive Cases in Haiti. (Masters Thesis). Rochester Institute of Technology. Retrieved from http://scholarworks.rit.edu/theses/9401

Chicago Manual of Style (16th Edition):

Young, Jessica. “Predicting Cholera Positive Cases in Haiti.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed July 22, 2017. http://scholarworks.rit.edu/theses/9401.

MLA Handbook (7th Edition):

Young, Jessica. “Predicting Cholera Positive Cases in Haiti.” 2017. Web. 22 Jul 2017.

Vancouver:

Young J. Predicting Cholera Positive Cases in Haiti. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2017 Jul 22]. Available from: http://scholarworks.rit.edu/theses/9401.

Council of Science Editors:

Young J. Predicting Cholera Positive Cases in Haiti. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: http://scholarworks.rit.edu/theses/9401

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