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Knowledge and Information Systems
Published in: Knowledge and Information Systems 3/2019

05-06-2018 | Regular Paper

Preferences-based learning of multinomial logit model

Author: Manish Aggarwal

Published in: Knowledge and Information Systems | Issue 3/2019

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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.
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Footnotes
1
The estimated PIS and NIS are different in each iteration depending upon the random selection of alternatives in \(\mathcal {A}_{train}\) and \(\mathcal {A}_{test}\).
 
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Metadata
Title
Preferences-based learning of multinomial logit model
Author
Manish Aggarwal
Publication date
05-06-2018
Publisher
Springer London
Published in
Knowledge and Information Systems / Issue 3/2019
Print ISSN: 0219-1377
Electronic ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-018-1215-9

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