Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/95656
Type of publication: Straipsnis recenzuojamoje Lietuvos tarptautinės konferencijos medžiagoje / Article in peer-reviewed Lithuanian international conference proceedings (P1e)
Field of Science: Informatika / Informatics (N009)
Author(s): Kurasova, Olga
Title: Visualization of support vectors
Is part of: The XIIIth international conference "Applied stochastic models and data analysis" ASMDA-2009 : selected papers : June 30 - July 3, 2009, Vilnius, Lithuania. Vilnius : Technika, 2009
Extent: P. 522-526
Date: 2009
Keywords: Support vectors;Multidimensional scaling;Classification;Visualization
ISBN: 9789955284635
Abstract: In this paper, some ways of visualization of support vectors are investigated. We examine a possibility to visualize support vectors by various methods, for example, Chernoff faces, Andrew’s curve, parallel coordinates, stars, etc. Since the changes of the classification quality are slight when comparing the results of classification of multidimensional data with that of two-dimensional data obtained by multidimensional scaling, it is possible to determine decision surfaces by analyzing the mapping data with a view to get more understandable results
Internet: http://www.vgtu.lt/leidiniai/leidykla/ASMDA_2009/23/23-104.htm
Affiliation(s): Matematikos ir informatikos institutas
Vytauto Didžiojo universitetas
Švietimo akademija
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

Files in This Item:
marc.xml4.6 kBXMLView/Open

MARC21 XML metadata

Show full item record
Export via OAI-PMH Interface in XML Formats
Export to Other Non-XML Formats

Page view(s)

38
checked on Mar 30, 2020

Download(s)

6
checked on Mar 30, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.