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Academic -- UNF -- Computing; MACHINE LEARNING; VISUALIZING; LEXICOGRAPHIC PREFERENCE TREES; DATA MINING; CLASSIFICATION; PREFERENCE LEARNING; Lexicographic preference trees -- Visualization; Preference visualization -- Web-based systems; Preference learning -- Genetic algorithms; Dynamic programming algorithms -- Design – Testing; Novel algorithms -- Design – Testing
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On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa
On Learning And Visualizing Lexicographic Preference Trees, Ahmed S. Moussa
UNF Graduate Theses and Dissertations
Preferences are very important in research fields such as decision making, recommendersystemsandmarketing. The focus of this thesis is on preferences over combinatorial domains, which are domains of objects configured with categorical attributes. For example, the domain of cars includes car objects that are constructed withvaluesforattributes, such as ‘make’, ‘year’, ‘model’, ‘color’, ‘body type’ and ‘transmission’.Different values can instantiate an attribute. For instance, values for attribute ‘make’canbeHonda, Toyota, Tesla or BMW, and attribute ‘transmission’ can haveautomaticormanual. To this end,thisthesis studiesproblemsonpreference visualization and learning for lexicographic preference trees, graphical preference models that often are compact over complex domains of objects built of …