Differential Evolution Classifier with Optimized Distance Measures from a Pool of Distances
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F12%3A86085128" target="_blank" >RIV/61989100:27740/12:86085128 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CEC.2012.6252889" target="_blank" >http://dx.doi.org/10.1109/CEC.2012.6252889</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2012.6252889" target="_blank" >10.1109/CEC.2012.6252889</a>
Alternative languages
Result language
angličtina
Original language name
Differential Evolution Classifier with Optimized Distance Measures from a Pool of Distances
Original language description
In this article we propose a differential evolution based nearest prototype classifier with extension to selecting the applied distance measure from a pool of alternative measures optimally for the particular data set at hand. The proposed method extendsthe earlier differential evolution based nearest prototype classifier by extending the optimization process to cover also the selection of distance measure instead of optimizing only the parameters related with a preselected and fixed distance measure.Now the optimization process is seeking also for the best distance measure providing the highest classification accuracy over the selected data set. It has been clear for some time that in classification, the usual euclidean distance measure is sometimesnot the best possible choice. Still usually not much has been done for it, and in many cases where some consideration to this problem is given, there has only been testing with a couple of alternative distance measures to find which one
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
2012 IEEE Congress on Evolutionary Computation (CEC), 2012
ISBN
978-1-4673-1509-8
ISSN
—
e-ISSN
—
Number of pages
7
Pages from-to
1-7
Publisher name
IEEE
Place of publication
New York
Event location
Brisbane
Event date
Jun 10, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000312859300034