This package is for version 3.7 of Bioconductor; for the stable, up-to-date release version, see GARS.
Bioconductor version: 3.7
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 (from within R,
enter citation("GARS")):
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("GARS")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("GARS")
| R Script | Titolo | |
| Reference Manual | ||
| Text | NEWS |
| biocViews | Classification, Clustering, FeatureExtraction, Software |
| Version | 1.0.0 |
| License | GPL (>= 2) |
| Depends | R (>= 3.5), ggplot2, cluster |
| Imports | DaMiRseq, MLSeq, stats, methods, SummarizedExperiment |
| LinkingTo | |
| Suggests | BiocStyle, knitr, testthat |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report |
Follow Installation instructions to use this package in your R session.
| Source Package | GARS_1.0.0.tar.gz |
| Windows Binary | GARS_1.0.0.zip |
| Mac OS X 10.11 (El Capitan) | GARS_1.0.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GARS |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GARS |
| Package Short Url | http://bioconductor.org/packages/GARS/ |
| Package Downloads Report | Download Stats |
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