Nonparametric Classification of Noisy Functions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10125854" target="_blank" >RIV/00216208:11320/12:10125854 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Nonparametric Classification of Noisy Functions
Original language description
The classification task for data coming from certain subspaces of continuous functions are discussed. This functions are of noisy nature and no further assumptions about the distributions are stated. Special attention is paid to depth-based classification and its possible generalizations. Several established depth functionals are compared. The outcoming drawbacks of these methods are fixed by considering the derivatives of the smoothed versions of functions, although the observations don't have to be differentiable itself.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
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 27th International Workshop on Statistical Modelling
ISBN
978-80-263-0250-6
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
233-238
Publisher name
Tribun EU
Place of publication
Brno
Event location
Praha
Event date
Jul 16, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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