<![CDATA[BOL: EFS: an ensemble feature selection tool implemented as R-package and web-application]]> https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application? https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application Tue, 28 Jan 2020 05:12:23 -0600 https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application <![CDATA[EFS: an ensemble feature selection tool implemented as R-package and web-application]]> The software EFS (Ensemble Feature Selection) makes use of multiple feature selection methods and combines their normalized outputs to a quantitative ensemble importance. Currently, eight different feature selection methods have been integrated in EFS, which can be used separately or combined in an ensemble.

https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0142-8

Address of the bookmark: http://efs.heiderlab.de/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application#item-annotation-3721 Tue, 28 Jan 2020 05:14:07 -0600 https://bioinformaticsonline.com/bookmarks/view/40721/efs-an-ensemble-feature-selection-tool-implemented-as-r-package-and-web-application#item-annotation-3721 <![CDATA[Comment by Jit]]> A review of ensembles for feature selection is described.

Current state-of-the-art is provided.

Types of ensembles, combination methods and evaluation measures are described.

Some challenges and future trends are provided.

all at https://www.sciencedirect.com/science/article/pii/S1566253518303440

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