Comparison Of Modern Clustering Algorithms For Two-Dimensional Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F14%3AA1501BBF" target="_blank" >RIV/61988987:17310/14:A1501BBF - 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
Comparison Of Modern Clustering Algorithms For Two-Dimensional Data
Original language description
Cluster analysis or clustering is a task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is the main taskof exploratory data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics.The topic of this paper is modern methods of clustering. The paper describes the theory needed to understand the principle of clustering and descriptions of algorithms used with clustering, followed by a comparison of the chosen methods.
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
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 28th European Conference on Modelling and Simulation ECMS 2014
ISBN
978-0-9564944-8-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
346-451
Publisher name
European Council for Modelling and Simulation
Place of publication
Sbr.-Dudweiler, Germany
Event location
Brescia, Italy
Event date
May 27, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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