Date of Award
2019
Document Type
Thesis
Degree Name
Bachelors
Department
Natural Sciences
First Advisor
Doucette, John
Area of Concentration
Computer Science
Abstract
Ordinal preferences indicate an agent's preferences over items in terms of alternative items, rather than on a quantitative scale. Modelling ordinal preferences is useful for the analysis of ranked choice voting for social choice and resource distribution as well as for the micro economic choice of consumer goods by an agent. This thesis uses a new methodology to compare the goodness of fit of preference models and applies it to the Mallows and Plackett-Luce model. Our findings show the Plackett-Luce model to have better goodness of fit in general, but the Mallows model to have a better score under certain information criterion. This thesis also proposes a new preference model using generative adversarial networks to create synthetic preference rankings given an arbitrary set of preferences. While this model was found to not output preferences, it may be useful with a more restrictive data representation.
Recommended Citation
Welden, Sawyer, "PERFORMANCE MEASURES FOR ASSESSING THE REALISM OF ORDINAL PREFERENCE MODELS" (2019). Theses & ETDs. 5838.
https://digitalcommons.ncf.edu/theses_etds/5838