Two-level clustering approach to training data instance selection: A case study for the steel industry

Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new knowledge from this information. However, when these databases becomes too large, it is not efficient to process all the availa...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Koskimaki, H., Juutilainen, I., Laurinen, P., Roning, J.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Biological system modeling Clustering algorithms Data models Distance measurement Predictive models Steel Training data
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