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Interactive Elicitation of a Majority Rule Sorting Model with Maximum Margin Optimization

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Book cover Algorithmic Decision Theory (ADT 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11834))

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Abstract

We consider the problem of eliciting a model for ordered classification. In particular, we consider Majority Rule Sorting (MR-sort), a popular model for multiple criteria decision analysis, based on pairwise comparisons between alternatives and idealized profiles representing the “limit” of each category.

Our interactive elicitation protocol asks, at each step, the decision maker to classify an alternative; these assignments are used as training set for learning the model. Since we wish to limit the cognitive burden of elicitation, we aim at asking informative questions in order to find a good approximation of the optimal classification in a limited number of elicitation steps. We propose efficient strategies for computing the next question and show how its computation can be formulated as a linear program. We present experimental results showing the effectiveness of our approach.

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Notes

  1. 1.

    This step is of course only to be performed in simulations, in real use of the procedure the classification error will not be known.

  2. 2.

    All experiments were run on a 2.9 GHz Intel, Core i7 and 16 Giga of RAM.

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Author information

Authors and Affiliations

  1. Université de Paris Dauphine, PSL Research University CNRS, LAMSADE, 75016, Paris, France

    Ons Nefla & Meltem Öztürk

  2. Emlyon Business School, 23 Avenue Guy de Collongue, Ecully, France

    Ons Nefla & Imène Brigui-Chtioui

  3. Sorbonne Université, CNRS, Laboratoire d’informatique de Paris 6, LIP6, 75005, Paris, France

    Paolo Viappiani

Authors
  1. Ons Nefla
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  2. Meltem Öztürk
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  3. Paolo Viappiani
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  4. Imène Brigui-Chtioui
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Correspondence to Ons Nefla .

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Editors and Affiliations

  1. Fuqua School of Business, Duke University, Durham, NC, USA

    Saša Pekeč

  2. Florida Institute for Human and Machine Cognition (IHMC), Pensacola, FL, USA

    Kristen Brent Venable

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Nefla, O., Öztürk, M., Viappiani, P., Brigui-Chtioui, I. (2019). Interactive Elicitation of a Majority Rule Sorting Model with Maximum Margin Optimization. In: Pekeč, S., Venable, K.B. (eds) Algorithmic Decision Theory. ADT 2019. Lecture Notes in Computer Science(), vol 11834. Springer, Cham. https://doi.org/10.1007/978-3-030-31489-7_10

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  • DOI: https://doi.org/10.1007/978-3-030-31489-7_10

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  • Online ISBN: 978-3-030-31489-7

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