Dimensionality reduction methods for biomedical data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F18%3A10391350" target="_blank" >RIV/00216208:11110/18:10391350 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/18:00491813
Result on the web
<a href="https://ojs.cvut.cz/ojs/index.php/CTJ/article/view/4425" target="_blank" >https://ojs.cvut.cz/ojs/index.php/CTJ/article/view/4425</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Dimensionality reduction methods for biomedical data
Original language description
The aim of this paper is to present basic principles of common multivariate statistical approaches to dimensionality reduction and to discuss three particular approaches, namely feature extraction, (prior) variable selection, and sparse variable selection. Their important examples are also presented in the paper, which includes the principal component analysis, minimum redundancy maximum relevance variable selection, and nearest shrunken centroid classifier with an intrinsic variable selection. Each of the three methods is illustrated on a real dataset with a biomedical motivation, including a biometric identification based on keystroke dynamics or a study of metabolomic profiles. Advantages and benefits of performing dimensionality reduction of multivariate data are discussed.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
30502 - Other medical science
Result continuities
Project
<a href="/en/project/NV15-29835A" target="_blank" >NV15-29835A: Graph-theory approach to complex organization and dynamics of human epileptic networks: implications for epilepsy surgery planning.</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Lékař a technika
ISSN
0301-5491
e-ISSN
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Volume of the periodical
48
Issue of the periodical within the volume
1
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
7
Pages from-to
29-35
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85049794593