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Fractal Based Data Separation in Data Mining

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F13%3A00389175" target="_blank" >RIV/67985807:_____/13:00389175 - isvavai.cz</a>

  • Result on the web

    <a href="http://sdiwc.net/digital-library/fractal-based-data-separation-in-data-mining" target="_blank" >http://sdiwc.net/digital-library/fractal-based-data-separation-in-data-mining</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fractal Based Data Separation in Data Mining

  • Original language description

    The separation of the searched data from the rest is an important task in data mining. Three separation/classification methods are presented. Considering data as points in a metric space, the methods are based on transformed distances of neighbors of a given point in a multidimensional space via a function that uses an estimate of scaling exponent. We shortly describe them and show that transformation function has form of the distance to the scaling exponent power. We also show the efficiency of methodspresented on artificial as well as on real-life tasks and compare them with other standard as well as advanced approaches.

  • 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/LG12020" target="_blank" >LG12020: Advanced statistical analysis and non-statistical separation techniques for physical processing detection in data sets sampled by means of elementary particle accelerators.</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

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

    Proceedings of the The Third International Conference on Digital Information Processing and Communications

  • ISBN

    978-0-9853483-3-5

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    287-295

  • Publisher name

    SDIWC

  • Place of publication

    Hong Kong

  • Event location

    Dubai

  • Event date

    Jan 30, 2013

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article