GARS

GARS: Genetic Algorithm for the identification of Robust Subsets of variables in high-dimensional and challenging datasets

Bioconductor version: 3.23 · Package version: 1.32.0

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.

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GARS")