LJELSR: A Strengthened Version of JELSR for Feature Selection and Clustering

Feature selection and sample clustering play an important role in bioinformatics. Traditional feature selection methods separate sparse regression and embedding learning. Later, to effectively identify the significant features of the genomic data, Joint Embedding Learning and Sparse Regression (JELS...

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Detalles Bibliográficos
Autores principales: Wu, Sha-Sha, Hou, Mi-Xiao, Feng, Chun-Mei, Liu, Jin-Xing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412528/
https://www.ncbi.nlm.nih.gov/pubmed/30781701
http://dx.doi.org/10.3390/ijms20040886

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412528/
https://www.ncbi.nlm.nih.gov/pubmed/30781701
http://dx.doi.org/10.3390/ijms20040886

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