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FuzzyClass: Fuzzy and Non-Fuzzy Classifiers

It provides classifiers which can be used for discrete variables and for continuous variables based on the Naive Bayes and Fuzzy Naive Bayes hypothesis. Those methods were developed by researchers belong to the 'Laboratory of Technologies for Virtual Teaching and Statistics (LabTEVE)' and 'Laboratory of Applied Statistics to Image Processing and Geoprocessing (LEAPIG)' at 'Federal University of Paraiba, Brazil'. They considered some statistical distributions and their papers were published in the scientific literature, as for instance, the Gaussian classifier using fuzzy parameters, proposed by 'Moraes, Ferreira and Machado' (2021) <doi:10.1007/s40815-020-00936-4>.

Version: 0.1.6
Depends: R (≥ 2.10)
Imports: caTools, doParallel, e1071, EnvStats, foreach, MASS, mvtnorm, parallel, purrr, Rdpack, rootSolve, stats, trapezoid
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, maxLik, dplyr
Published: 2024-02-14
DOI: 10.32614/CRAN.package.FuzzyClass
Author: Jodavid Ferreira ORCID iD [aut, cre], Ronei Moraes ORCID iD [ctb], Arthur Ricardo [ctb]
Maintainer: Jodavid Ferreira <jodavid at protonmail.com>
BugReports: https://github.com/leapigufpb/FuzzyClass/issues
License: MIT + file LICENSE
URL: https://github.com/leapigufpb/FuzzyClass
NeedsCompilation: no
Language: en-US
Citation: FuzzyClass citation info
Materials: README NEWS
CRAN checks: FuzzyClass results

Documentation:

Reference manual: FuzzyClass.pdf
Vignettes: FuzzyClass
FuzzyClassSolvingProblem

Downloads:

Package source: FuzzyClass_0.1.6.tar.gz
Windows binaries: r-devel: FuzzyClass_0.1.6.zip, r-release: FuzzyClass_0.1.6.zip, r-oldrel: FuzzyClass_0.1.6.zip
macOS binaries: r-release (arm64): FuzzyClass_0.1.6.tgz, r-oldrel (arm64): FuzzyClass_0.1.6.tgz, r-release (x86_64): FuzzyClass_0.1.6.tgz, r-oldrel (x86_64): FuzzyClass_0.1.6.tgz
Old sources: FuzzyClass archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FuzzyClass to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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