Adapting to drift in continuous domains (Extended abstract) View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

1995

AUTHORS

Miroslav Kubat , Gerhard Widmer

ABSTRACT

The experiments demonstrate that FRANN compares favourably with FLORA4 in the presence of concept drift. Learning is possible from examples described by symbolic as well as by numeric attributes, and because of its representation formalism (RBF networks, which realize a kind of prototype weighting scheme) FRANN is particularly effective in capturing concepts with nonlinear boundaries. More... »

PAGES

307-310

Book

TITLE

Machine Learning: ECML-95

ISBN

978-3-540-59286-0
978-3-540-49232-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-59286-5_74

DOI

http://dx.doi.org/10.1007/3-540-59286-5_74

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1009791448


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