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MORD: Multi-class Classifier for Ordinal Regression

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211706" target="_blank" >RIV/68407700:21230/13:00211706 - isvavai.cz</a>

  • Result on the web

    <a href="http://cmp.felk.cvut.cz/pub/cmp/articles/antoniuk/Antoniuk-Franc-Hlavac-ECML-2013.pdf" target="_blank" >http://cmp.felk.cvut.cz/pub/cmp/articles/antoniuk/Antoniuk-Franc-Hlavac-ECML-2013.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-642-40994-3_7" target="_blank" >10.1007/978-3-642-40994-3_7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    MORD: Multi-class Classifier for Ordinal Regression

  • Original language description

    We show that classification rules used in ordinal regression are equivalent to a certain class of linear multi-class classifiers. This observation not only allows to design new learning algorithms for ordinal regression using existing methods for multi-class classification but it also allows to derive new models for ordinal regression. For example, one can convert learning of ordinal classifier with (almost) arbitrary loss function to a convex unconstrained risk minimization problem for which many efficient solvers exist. The established equivalence also allows to increase discriminative power of the ordinal classifier without need to use kernels by introducing a piece-wise ordinal classifier. We demonstrate advantages of the proposed models on standard benchmarks as well as in solving a real-life problem. In particular, we show that the proposed piece-wise ordinal classifier applied to visual age estimation outperforms other standard prediction models.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Machine Learning and Knowledge Discovery in Databases

  • ISBN

    978-3-642-40993-6

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    16

  • Pages from-to

    96-111

  • Publisher name

    Springer-Verlag, GmbH

  • Place of publication

    Heidelberg

  • Event location

    Prague

  • Event date

    Sep 23, 2013

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article