Cargando…
A novel framework based on the multi-label classification for dynamic selection of classifiers
Multi-classifier systems (MCSs) are some kind of predictive models that classify instances by combining the output of an ensemble of classifiers given in a pool. With the aim of enhancing the performance of MCSs, dynamic selection (DS) techniques have been introduced and applied to MCSs. Dealing wit...
Autores principales: | Elmi, Javad, Eftekhari, Mahdi, Mehrpooya, Adel, Ravari, Mohammad Rezaei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9806828/ https://www.ncbi.nlm.nih.gov/pubmed/36618577 http://dx.doi.org/10.1007/s13042-022-01751-z |
Ejemplares similares
-
Partial Classifier Chains with Feature Selection by Exploiting Label Correlation in Multi-Label Classification
por: Wang, Zhenwu, et al.
Publicado: (2020) -
Decoding Clinical Biomarker Space of COVID-19: Exploring Matrix Factorization-based Feature Selection Methods
por: Saberi-Movahed, Farshad, et al.
Publicado: (2021) -
Decoding clinical biomarker space of COVID-19: Exploring matrix factorization-based feature selection methods
por: Saberi-Movahed, Farshad, et al.
Publicado: (2022) -
Identification of Multi-Functional Enzyme with Multi-Label Classifier
por: Che, Yuxin, et al.
Publicado: (2016) -
ColpoClassifier: A Hybrid Framework for Classification of the Cervigrams
por: Kalbhor, Madhura, et al.
Publicado: (2023)