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Mixture-based Clustering Non-gaussian Data with Fixed Bounds

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00462336" target="_blank" >RIV/67985556:_____/16:00462336 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/IS.2016.7737431" target="_blank" >http://dx.doi.org/10.1109/IS.2016.7737431</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/IS.2016.7737431" target="_blank" >10.1109/IS.2016.7737431</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Mixture-based Clustering Non-gaussian Data with Fixed Bounds

  • Original language description

    This paper deals with clustering non-gaussian data with fixed bounds. It considers the problem using recursive mixture estimation algorithms under the Bayesian methodology. Such a solution is often desired in areas, where the assumption of normality of modeled data is rather questionable and brings a series of limitations (e.g., non-negative, bounded data, etc.). Here for modeling the data a mixture of uniform distributions is taken, where individual clusters are described by mixture components. For the on-line detection of clusters of measured bounded data, the paper proposes a mixture estimation algorithm based on (i) the update of reproducible statistics of uniform components; (ii) the heuristic initialization via the method of moments; (iii) the non-trivial adaptive forgetting technique; (iv) the data-dependent dynamic pointer model. The approach is validated using realistic traffic flow simulations.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA15-03564S" target="_blank" >GA15-03564S: Clustering and classification using recursive mixture estimation</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2016

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 2016 IEEE 8th International Conference on Intelligent Systems

  • ISBN

    978-1-5090-1353-1

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    265-271

  • Publisher name

    IEEE

  • Place of publication

    Sofia

  • Event location

    Sofia

  • Event date

    Sep 4, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000391554300037