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PEARL: Probabilistic Exact Adaptive Random Forest with Lossy Counting for Data Streams

In order to adapt random forests to the dynamic nature of data streams, the state-of-the-art technique discards trained trees and grows new trees when concept drifts are detected. This is particularly wasteful when recurrent patterns exist. In this work, we introduce a novel framework called PEARL,...

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Detalles Bibliográficos
Autores principales: Wu, Ocean, Koh, Yun Sing, Dobbie, Gillian, Lacombe, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206241/
http://dx.doi.org/10.1007/978-3-030-47436-2_2

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