Learning of Utilitarian Decision Model through Preferences

Manish Aggarwal

No WP2016-02-12, IIMA Working Papers from Indian Institute of Management Ahmedabad, Research and Publication Department

Abstract: Understanding and predicting the decision making behaviour of individuals is a subject of interest for marketers, strategists, economists and the computer scientists alike. We develop an aproach to learn a decision maker (DM)’s behavioral process by combining recent possibilistic discrete choice models with the emerging machine learning methods. The proposed approach considers the utility values derived by a DM from each of the attribute values (information source values). We take the training information in the form of the exemplary multi-attribute preferences, and the decision model is specified in terms of two vectors that are unique to a DM. The experimental results on a set of 10 benchmark datasets suggest that our approach is both intuitively appealing and competitive to state-of-the-art methods in terms of the prediction accuracy.

Date: 2016-03-04
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Persistent link: https://EconPapers.repec.org/RePEc:iim:iimawp:14427

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