Some Regularized Tools for Dimensionality Reduction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F25%3A00642337" target="_blank" >RIV/67985807:_____/25:00642337 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-032-03708-4_20" target="_blank" >https://doi.org/10.1007/978-3-032-03708-4_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-032-03708-4_20" target="_blank" >10.1007/978-3-032-03708-4_20</a>
Alternative languages
Result language
angličtina
Original language name
Some Regularized Tools for Dimensionality Reduction
Original language description
Dimensionality reduction has become a commonly used part of the analysis of complex economic data. The aim of this work is to study the potential of regularized tools for dimensionality reduction methods and possibly to propose some novel regularized tools. The regularization in the form of shrinkage allows to improve numerical stability of the tools for high-dimensional data and also to reduce variability of parameter estimates at the cost of introducing bias. Firstly, a robust regularized version of the coefficient of multiple correlation is proposed, which may be exploited within a Minimum Relevance Maximum Redundancy supervised variable selection. Secondly, the ridge regularization is discussed not to bring any modification of principal component analysis, this is true also for robust versions of principal component analysis.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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/GA25-15490S" target="_blank" >GA25-15490S: LEDNeCo: Low Energy Deep Neurocomputing</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Intelligence and Soft Computing. 24th International Conference ICAISC 2025, Proceedings Part II
ISBN
978-3-032-03707-7
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
243-253
Publisher name
Springer
Place of publication
Cham
Event location
Zakopane
Event date
Jun 22, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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