Please use this identifier to cite or link to this item:
http://hdl.handle.net/11718/23039
Title: | Preferences-based learning of multinomial logit model |
Authors: | Aggarwal, Manish |
Keywords: | Preference learning Decision behavior Choice modeling Multi-attribute decision making |
Issue Date: | 2019 |
Publisher: | Springer |
Citation: | Aggarwal, M. (2019). Preferences-based learning of multinomial logit model. Knowledge and Information Systyems, 59(3), 523-538. doi:https://doi.org/10.1007/s10115-018-1215-9 |
Abstract: | We learn the parameters of the popular multinomial logit model to gain insights about a DM’s decision process. We accomplish this objective through the recent algorithmic advances in the emerging field of preference learning. The empirical evaluation of the proposed approach is performed on a set of 12 publicly available benchmark datasets. First experimental results suggest that our approach is not only intuitively appealing, but also competitive to state-of-the-art preference learning methods in terms of the prediction accuracy. |
URI: | http://hdl.handle.net/11718/23039 |
ISSN: | 0219-3116 |
Appears in Collections: | Journal Articles |
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