Clustering is the process of grouping objects based on some notion of similarity. It is commonly applied for exploratory data analysis, segmentation, preprocessing and data summarization.Traditional clustering algorithms only find one clustering solution. However, data can be grouped and interpreted in many different ways. Moreover, different clustering solutions are interesting for different purposes. Instead of committing to one clustering solution, here we introduce four methods that can provide several possible alternative clustering solutions to the user for exploratory data analysis.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Niu DonglinDonglin Niu received Bachelor degree in Nanjing University, China and PhD degree in Northeastern University, Boston, in electrical engineering. His interest includes machine learning, web scale data mining, distributed com. N° de réf. du vendeur 4999832
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Taschenbuch. Etat : Neu. Multiple alternative clusterings and dimensionality reduction | Theory and application | Donglin Niu | Taschenbuch | Englisch | Scholar's Press | EAN 9783639718867 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 105220276
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Clustering is the process of grouping objects based on some notion of similarity. It is commonly applied for exploratory data analysis, segmentation, preprocessing and data summarization.Traditional clustering algorithms only find one clustering solution. However, data can be grouped and interpreted in many different ways. Moreover, different clustering solutions are interesting for different purposes. Instead of committing to one clustering solution, here we introduce four methods that can provide several possible alternative clustering solutions to the user for exploratory data analysis. N° de réf. du vendeur 9783639718867
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