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Knowledge acquisition combining analytical and empirical techniques

Autor
Martin, M.; Sangüesa, R.; Cortes, U.
Tipus d'activitat
Presentació treball a congrés
Nom de l'edició
Eighth International Workshop on Machine Learning
Any de l'edició
1991
Llibre d'actes
Machine Learning: proceedings of the Eighth International Workshop on Machine Learning (ML91)
Pàgina inicial
657
Pàgina final
661
Resum
The authors introduce a methodology for classification-oriented knowledge-base generation using LINNEO, software for fuzzy classification and rule generation which resorts to analytical-EBG-and empirical -SBL- knowledge acquisition techniques. LINNEO builds a classification from a set of (frequently noisy) observations and a (possibly incomplete) domain theory supplied by the expert. The final result is a fuzzy rules knowledge base. It is believed that integrating both types (EBG, SBL) of learni...
Paraules clau
Fuzzy Logic, Knowledge Acquisition, Learning (artificial Intelligence)
Grup de recerca
IDEAI-UPC Intelligent Data Science and Artificial Intelligence
KEMLG - Grup d´Enginyeria del Coneixement i Aprenentatge Automàtic

Participants