All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Implicitly Weighted Robust Classification Applied to Brain Activity Research

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00473143" target="_blank" >RIV/67985807:_____/17:00473143 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-54717-6_6" target="_blank" >http://dx.doi.org/10.1007/978-3-319-54717-6_6</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-54717-6_6" target="_blank" >10.1007/978-3-319-54717-6_6</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Implicitly Weighted Robust Classification Applied to Brain Activity Research

  • Original language description

    In bioinformatics, regularized linear discriminant analysis is commonly used as a tool for supervised classification problems tailor-made for high-dimensional data with the number of variables exceeding the number of observations. However, its various available versions are too vulnerable to the presence of outlying measurements in the data. In this paper, we exploit principles of robust statistics to propose new versions of regularized linear discriminant analysis suitable for high-dimensional data contaminated by (more or less) severe outliers. The work exploits a regularized version of the minimum weighted covariance determinant estimator, which is one of highly robust estimators of multivariate location and scatter. The performance of the novel classification methods is illustrated on real data sets with a detailed analysis of data from brain activity research.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA13-23940S" target="_blank" >GA13-23940S: Personality and spontaneous brain activity during rest and movie watching: relation and structural determinants</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Biomedical Engineering Systems and Technologies

  • ISBN

    978-3-319-54716-9

  • ISSN

    1865-0929

  • e-ISSN

  • Number of pages

    21

  • Pages from-to

    87-107

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Rome

  • Event date

    Feb 21, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article