- recipe bioconductor-fcbf
Fast Correlation Based Filter for Feature Selection
MIT + file LICENSE
This package provides a simple R implementation for the Fast Correlation Based Filter described in Yu, L. and Liu, H.; Feature Selection for High-Dimensional Data: A Fast Correlation Based Filter Solution,Proc. 20th Intl. Conf. Mach. Learn. (ICML-2003), Washington DC, 2003 The current package is an intent to make easier for bioinformaticians to use FCBF for feature selection, especially regarding transcriptomic data.This implies discretizing expression (function discretize_exprs) before calculating the features that explain the class, but are not predictable by other features. The functions are implemented based on the algorithm of Yu and Liu, 2003 and Rajarshi Guha's implementation from 13/05/2005 available (as of 26/08/2018) at http://www.rguha.net/code/R/fcbf.R .
- package bioconductor-fcbf¶
- depends bioconductor-summarizedexperiment:
- depends r-base:
- depends r-ggplot2:
- depends r-gridextra:
- depends r-mclust:
- depends r-pbapply:
While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.
Given that you already have a conda environment in which you want to have this package, install with:
mamba install bioconductor-fcbf and update with:: mamba update bioconductor-fcbf
To create a new environment, run:
mamba create --name myenvname bioconductor-fcbf
myenvnamebeing a reasonable name for the environment (see e.g. the mamba docs for details and further options).
Alternatively, use the docker container:
docker pull quay.io/biocontainers/bioconductor-fcbf:<tag> (see `bioconductor-fcbf/tags`_ for valid values for ``<tag>``)