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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "praznik" in publications use:'
type: software
license: GPL-3.0-only
title: 'praznik: Tools for Information-Based Feature Selection and Scoring'
version: 11.0.0
identifiers:
- type: doi
  value: 10.32614/CRAN.package.praznik
abstract: A toolbox of fast, native and parallel implementations of various information-based
  importance criteria estimators and feature selection filters based on them, inspired
  by the overview by Brown, Pocock, Zhao and Lujan (2012) <https://www.jmlr.org/papers/v13/brown12a.html>.
  Contains, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng,
  Long and Ding (2005) <https://doi.org/10.1109/TPAMI.2005.159>; joint mutual information
  ('JMI') method by Yang and Moody (1999) <https://papers.nips.cc/paper/1779-data-visualization-and-feature-selection-new-algorithms-for-nongaussian-data>;
  double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006)
  <https://doi.org/10.1007/11732242_9> as well as joint mutual information maximisation
  ('JMIM') method by Bennasar, Hicks and Setchi (2015) <https://doi.org/10.1016/j.eswa.2015.07.007>.
authors:
- family-names: Kursa
  given-names: Miron B.
  email: m@mbq.me
  orcid: https://orcid.org/0000-0001-7672-648X
preferred-citation:
  type: article
  title: 'Praznik: High performance information-based feature selection'
  authors:
  - family-names: Kursa
    given-names: Miron B.
    email: m@mbq.me
    orcid: https://orcid.org/0000-0001-7672-648X
  journal: SoftwareX
  year: '2021'
  volume: '16'
  url: https://doi.org/10.1016/j.softx.2021.100819
  start: '100819'
repository: https://CRAN.R-project.org/package=praznik
repository-code: https://gitlab.com/mbq/praznik
url: https://gitlab.com/mbq/praznik
date-released: '2022-05-20'
contact:
- family-names: Kursa
  given-names: Miron B.
  email: m@mbq.me
  orcid: https://orcid.org/0000-0001-7672-648X
references:
- type: article
  title: Kendall transformation brings a robust categorical representation of ordinal
    data
  authors:
  - family-names: Kursa
    given-names: Miron B.
  journal: Scientific Reports
  year: '2022'
  volume: '12'
  url: https://doi.org/10.1038/s41598-022-12224-2
  start: '8341'