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Cluster discovery in environmental databases using GESCONDA: the added value of comparisons

Autor
Gibert, Karina; Sànchez-Marrè, M.; Flores, X.
Tipus d'activitat
Article en revista
Revista
AI communications: the european journal of artificial intelligence
Data de publicació
2005-12
Volum
18
Número
4
Pàgina inicial
319
Pàgina final
331
URL
http://content.iospress.com/articles/ai-communications/aic353 Obrir en finestra nova
Resum
Clustering techniques have a great importance in knowledge discovery because they can find out new groups or clusters of objects within databases. Thus, they are unsupervised learning methods, very useful when facing unknown, unlabelled and ill-structured databases, as environmental databases are. In this paper, different clustering algorithms are analyzed and compared. They are used on a real environmental data set in order to study their impact in characterizing states in this kind of domains....
Paraules clau
Knowledge acquisition and management, cluster validation, clustering, data mining, environmental databases, machine learning, statistical modelling, wastewater treatment plant
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
KEMLG - Grup d´Enginyeria del Coneixement i Aprenentatge Automàtic

Participants