Feature construction and parameter setting for Support Vector Machines
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F03%3A00009614" target="_blank" >RIV/00216224:14330/03:00009614 - 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
Feature construction and parameter setting for Support Vector Machines
Original language description
Support Vector Machines (SVM) are a machine learning algorithm that can be used for both classification and regression problems. In this paper, we focus on two problems with SVM. First, we concentrate on the parameter setting of SVM which has great influence on the performance. Then feature construction is discussed. Features can be used to improve results of SVM and to represent structured data in SVM. Mining frequent patterns from structured data is used to construct features.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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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
Proceedings of the 2nd Conference Znalosti 2003
ISBN
80-248-0229-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
327-332
Publisher name
VŠB-TUO, Ostrava
Place of publication
Ostrava
Event location
Ostrava
Event date
Jan 1, 2003
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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