Cargando…
A Framework for Feature Selection to Exploit Feature Group Structures
Filter feature selection methods play an important role in machine learning tasks when low computational costs, classifier independence or simplicity is important. Existing filter methods predominantly focus only on the input data and do not take advantage of the external sources of correlations wit...
Autores principales: | Perera, Kushani, Chan, Jeffrey, Karunasekera, Shanika |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206161/ http://dx.doi.org/10.1007/978-3-030-47426-3_61 |
Ejemplares similares
-
Group Based Unsupervised Feature Selection
por: Perera, Kushani, et al.
Publicado: (2020) -
Image Analysis Enhanced Event Detection from Geo-Tagged Tweet Streams
por: Han, Yi, et al.
Publicado: (2020) -
BillionCOV: An enriched billion-scale collection of COVID-19 tweets for efficient hydration
por: Lamsal, Rabindra, et al.
Publicado: (2023) -
A Robust and Integrated Visual Odometry Framework Exploiting the Optical Flow and Feature Point Method
por: Qiu, Haiyang, et al.
Publicado: (2023) -
Review of feature selection approaches based on grouping of features
por: Kuzudisli, Cihan, et al.
Publicado: (2023)