Greedy Algorithm for a Training Set Reduction in the Kernel Methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F03%3A03091283" target="_blank" >RIV/68407700:21230/03:03091283 - 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
Greedy Algorithm for a Training Set Reduction in the Kernel Methods
Original language description
We propose a technique for a training set approximation and its usage in kernel methods. The approach aims to represent data in a low dimensional space with possibly minimal representation error which is similar to the Principal Component Analysis (PCA).In contrast to the PCA, the basis vectors of the low dimensional space used for data representation are properly selected vectors from the training set and not as their linear combinations. The basis vectors can be selected by a simple algorithm which has low computational requirements and allows on-line processing of huge data sets. The proposed method was used to approximate training sets of the Support Vector Machines and Kernel Fisher Linear Discriminant which are known method for learning classifiers. The experiments show that the proposed approximation can significantly reduce the complexity of the found classifiers (the number of the support vectors) while retaining their accuracy.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F03%2F0440" target="_blank" >GA102/03/0440: Recognizing human activities for automated video surveillance</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CAIP 2003: Computer Analysis of Images and Patterns
ISBN
3-540-40730-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
426-433
Publisher name
Springer
Place of publication
Berlin
Event location
Groningen
Event date
Aug 25, 2003
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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