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Record type:
stať ve sborníku (D)
Home Department:
Katedra informatiky a počítačů (31400)
Title:
Unconventional Methods for Clustering
Citace
Kotyrba, M. Unconventional Methods for Clustering.
In:
International Conference on Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015): PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2015 (ICNAAM-2015) 2015-09-23 Rhodes, GREECE.
AMER INST PHYSICS, 2016. ISBN 978-0-7354-1392-4.
Subtitle
Publication year:
2016
Obor:
Informatika
Number of pages:
4
Page from:
neuvedeno
Page to:
neuvedeno
Form of publication:
Tištená verze
ISBN code:
978-0-7354-1392-4
ISSN code:
0094-243X
Proceedings title:
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2015 (ICNAAM-2015)
Proceedings:
Mezinárodní
Publisher name:
AMER INST PHYSICS
Place of publishing:
neuvedeno
Country of Publication:
Sborník vydaný v zahraničí
Název konference:
International Conference on Numerical Analysis and Applied Mathematics 2015 (ICNAAM 2015)
Místo konání konference:
Rhodes, GREECE
Datum zahájení konference:
Typ akce podle státní
příslušnosti účastníků:
Celosvětová akce
WoS code:
000380803300132
EID:
2-s2.0-84984560556
Key words in English:
Cluster analysis; Self Organising Map Algorithm
Annotation in original language:
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 task of 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 one of the modern methods of clustering namely SOM (Self Organising Map). The paper describes the theory needed to understand the principle of clustering and descriptions of algorithm used with clustering in our experiments.
Annotation in english language:
References
Reference
R01:
RIV/61988987:17310/16:A1701IGR
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