On Learning of Choice Models with Interactive Attributes
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On Learning of Choice Models with Interactive Attributes
Abstract—Introducing recent advances in the machine learning techniques to state-of-the-art discrete choice models, we develop an approach to infer the unique and complex decision making process of a decision-maker (DM), which is characterized by the DM’s priorities and attitudinal character, along with the attributes interaction, to name a few. < final year projects >
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