Data Mining with Clustering

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F08%3A63507644" target="_blank" >RIV/70883521:28120/08:63507644 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
čeština
Original language name
Shlukovací metody v data miningu.
Original language description
One of the oppotunities in data mining is a use of clustering analysis. Clustering analysis belongs to unsupervised methods of data mining. We put here a focus on this method. Some basic principles are described in the second part of this paper. This method is examined on two examples from the marketing field. In the first example is used software Statgraphics 5.0Plus to solve clustering problem (nearest neighbour algorithm and Eucleidian distance); and in the second example is used Statistica 6.0Cz software (from Statoft; Inc.).
Czech name
Shlukovací metody v data miningu.
Czech description
One of the oppotunities in data mining is a use of clustering analysis. Clustering analysis belongs to unsupervised methods of data mining. We put here a focus on this method. Some basic principles are described in the second part of this paper. This method is examined on two examples from the marketing field. In the first example is used software Statgraphics 5.0Plus to solve clustering problem (nearest neighbour algorithm and Eucleidian distance); and in the second example is used Statistica 6.0Cz software (from Statoft; Inc.).

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AE - Management, administration and clerical work
OECD FORD branch
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Publication year
2008
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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