Cargando…
An Adaptive Heterogeneous Online Learning Ensemble Classifier for Nonstationary Environments
In recent years, the prevalence of technological advances has led to an enormous and ever-increasing amount of data that are now commonly available in a streaming fashion. In such nonstationary environments, the underlying process generating the data stream is characterized by an intrinsic nonstatio...
Autores principales: | Museba, Tinofirei, Nelwamondo, Fulufhelo, Ouahada, Khmaies |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7987417/ https://www.ncbi.nlm.nih.gov/pubmed/33815495 http://dx.doi.org/10.1155/2021/6669706 |
Ejemplares similares
-
Analysis of Nonstationary Radiometer Gain Using Ensemble Detection
por: Aksoy, Mustafa, et al.
Publicado: (2020) -
Investigating Random Linear Coding from a Pricing Perspective
por: Zhu, Hailing, et al.
Publicado: (2018) -
Design of adaptive ensemble classifier for online sentiment analysis and opinion mining
por: Kumar, Sanjeev, et al.
Publicado: (2021) -
Learned-SBL-GAMP based hybrid precoders/combiners in millimeter wave massive MIMO systems
por: Ali K., Shoukath, et al.
Publicado: (2023) -
Smart Meter Data Collection Using Public Taxis
por: Ngandu, Kabeya Gilbert, et al.
Publicado: (2018)