sigFeature
This is the development version of sigFeature; for the stable release version, see sigFeature.
sigFeature: Significant feature selection using SVM-RFE & t-statistic
Bioconductor version: Development (3.21)
This package provides a novel feature selection algorithm for binary classification using support vector machine recursive feature elimination SVM-RFE and t-statistic. In this feature selection process, the selected features are differentially significant between the two classes and also they are good classifier with higher degree of classification accuracy.
Author: Pijush Das Developer [aut, cre], Dr. Susanta Roychudhury User [ctb], Dr. Sucheta Tripathy User [ctb]
Maintainer: Pijush Das Developer <topijush at gmail.com>
citation("sigFeature")
):
Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("sigFeature")
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("sigFeature")
sigFeature | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Classification, FeatureExtraction, GeneExpression, GenePrediction, Microarray, Normalization, Software, SupportVectorMachine, Transcription, mRNAMicroarray |
Version | 1.25.0 |
In Bioconductor since | BioC 3.8 (R-3.5) (6 years) |
License | GPL (>= 2) |
Depends | R (>= 3.5.0) |
Imports | biocViews, nlme, e1071, openxlsx, pheatmap, RColorBrewer, Matrix, SparseM, graphics, stats, utils, SummarizedExperiment, BiocParallel, methods |
System Requirements | |
URL |
See More
Suggests | RUnit, BiocGenerics, knitr, rmarkdown |
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 | sigFeature_1.25.0.tar.gz |
Windows Binary (x86_64) | sigFeature_1.25.0.zip (64-bit only) |
macOS Binary (x86_64) | sigFeature_1.25.0.tgz |
macOS Binary (arm64) | sigFeature_1.25.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/sigFeature |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/sigFeature |
Bioc Package Browser | https://code.bioconductor.org/browse/sigFeature/ |
Package Short Url | https://bioconductor.org/packages/sigFeature/ |
Package Downloads Report | Download Stats |