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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "GARS" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'GARS: GARS: Genetic Algorithm for the identification of Robust Subsets of
  variables in high-dimensional and challenging datasets'
version: 1.25.0
doi: 10.1186/s12859-020-3400-6
abstract: '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.'
authors:
- family-names: Chiesa
  given-names: Mattia
  email: mattia.chiesa@hotmail.it
- family-names: Piacentini
  given-names: Luca
  email: luca.piacentini@cardiologicomonzino.it
preferred-citation:
  type: article
  title: 'GARS: Genetic Algorithm for the identification of a Robust Subset of features
    in high-dimensional datasets'
  authors:
  - family-names: Chiesa
    given-names: Mattia
    email: mattia.chiesa@hotmail.it
  - family-names: Maioli
    given-names: Giada
  - family-names: Colombo
    given-names: Gualtiero I.
  - family-names: Piacentini
    given-names: Luca
    email: luca.piacentini@cardiologicomonzino.it
  journal: BMC bioinformatics
  volume: '21'
  issue: '1'
  year: '2020'
  doi: 10.1186/s12859-020-3400-6
  start: '54'
repository: https://bioc.r-universe.dev
date-released: '2020-09-04'
contact:
- family-names: Chiesa
  given-names: Mattia
  email: mattia.chiesa@hotmail.it