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Adaptive parameter-free learning from evolving data streams

Autor
Bifet, A.C.; Gavaldà, R.
Tipus d'activitat
Document cientificotècnic
Data
2009-03
Codi
LSI-09-9-R
Repositori
http://hdl.handle.net/2117/87914 Obrir en finestra nova
Resum
We propose and illustrate a method for developing algorithms that can adaptively learn from data streams that change over time. As an example, we take Hoeffding Tree, an incremental decision tree inducer for data streams, and use as a basis it to build two new methods that can deal with distribution and concept drift: a sliding window-based algorithm, Hoeffding Window Tree, and an adaptive method, Hoeffding Adaptive Tree. Our methods are based on using change detectors and estimator modules at t...
Citació
Bifet, A.C., Gavaldà, R. "Adaptive parameter-free learning from evolving data streams". 2009.
Paraules clau
Concept drift, Data mining, Data streams, Decision trees
Grup de recerca
LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge

Participants

Arxius