GARS
This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see GARS.
GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets
Bioconductor version: 3.9
Feature selection aims to identify and remove redundant, irrelevant and noisy variables from high-dimensional datasets. Selecting informative features affects the subsequent classification and regression analyses by improving their overall performances. Several methods have been proposed to perform feature selection: most of them relies on univariate statistics, correlation, entropy measurements or the usage of backward/forward regressions. Herein, we propose an efficient, robust and fast method that adopts stochastic optimization approaches for high-dimensional. GARS is an innovative implementation of a genetic algorithm that selects robust features in high-dimensional and challenging datasets.
Author: Mattia Chiesa <mattia.chiesa at hotmail.it>, Luca Piacentini <luca.piacentini at cardiologicomonzino.it>
Maintainer: Mattia Chiesa <mattia.chiesa at hotmail.it>
citation("GARS")
):
Installation
To install this package, start R (version "3.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GARS")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GARS")
Titolo | R Script | |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Classification, Clustering, FeatureExtraction, Software |
Version | 1.4.0 |
In Bioconductor since | BioC 3.7 (R-3.5) (6 years) |
License | GPL (>= 2) |
Depends | R (>= 3.5), ggplot2, cluster |
Imports | DaMiRseq, MLSeq, stats, methods, SummarizedExperiment |
System Requirements | |
URL |
See More
Suggests | BiocStyle, knitr, testthat |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | GARS_1.4.0.tar.gz |
Windows Binary | GARS_1.4.0.zip |
Mac OS X 10.11 (El Capitan) | GARS_1.4.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/GARS |
Source Repository (Developer Access) | git clone [email protected]:packages/GARS |
Bioc Package Browser | https://code.bioconductor.org/browse/GARS/ |
Package Short Url | https://bioconductor.org/packages/GARS/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.9 | Source Archive |