Example for Determining of Metrics (Degree of Dissimilarity) of Objects Cluster Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23210%2F13%3A43920919" target="_blank" >RIV/49777513:23210/13:43920919 - 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
Example for Determining of Metrics (Degree of Dissimilarity) of Objects Cluster Analysis
Original language description
Similarity resp. dissimilarity of objects is a basic principle of cluster analysis. Similarity (dissimilarity) can be determined by degree of distance, degree of correlation and degree of association. This paper describes the method of determining the metrics, which are the most common degree of similarity used in the cluster analysis. Procedure for determining the metrics are exemplified.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BA - General mathematics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2013 International Conference on Frontiers of Energy, Environmental Materials and Civil Engineering (FEEMCE 2013)
ISBN
978-1-60595-142-3
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
317-320
Publisher name
DEStech Publications
Place of publication
Shanghai
Event location
Shanghai, China
Event date
Nov 21, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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