Classification Model Based on Kohonen Maps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F18%3A43898583" target="_blank" >RIV/60076658:12310/18:43898583 - isvavai.cz</a>
Result on the web
<a href="http://ceur-ws.org/Vol-2300/Paper35.pdf" target="_blank" >http://ceur-ws.org/Vol-2300/Paper35.pdf</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Classification Model Based on Kohonen Maps
Original language description
The standard Kohonen map uses unsupervised learning and single Kohonen layer, which allows the usage for clustering and visualization. The number of model parameters is relatively small and their settings are therefore not so complicated. The aim of this paper is to introduce three modifications of this basic model so that it can be used for classification tasks. The first change is the transition to supervised learning by adding input data about the required outputs. The second modification is the implementation of the hierarchical model structure to improve the classification results. The third extension is the implementation of an optimization mechanism for setting the parameters of the model because the number of model parameters was extended and their adjustment was more difficult. The results of the experiments with modified model will be presented too.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Conference Proceedings ADVANCED COMPUTER INFORMATION TECHNOLOGIES ACIT 2018
ISBN
—
ISSN
1613-0073
e-ISSN
neuvedeno
Number of pages
4
Pages from-to
145-148
Publisher name
Ternopil National Economic University
Place of publication
Ternopil, Ukraine
Event location
Ceske Budejovice, Czech Republic
Event date
Jun 1, 2018
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—