fmf: Fast Class Noise Detector with Multi-Factor-Based Learning

A fast class noise detector which provides noise score for each observations. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations.

Version: 1.1.1
Depends: R (≥ 2.10.0)
Imports: Rcpp, caret, solitude, kernlab, C50, e1071, FactoMineR, dplyr, factoextra, ggplot2
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr, knitr, rmarkdown
Published: 2020-09-03
Author: Wanwan Zheng [aut, cre], Mingzhe Jin [aut], Lampros Mouselimis [ctb, cph]
Maintainer: Wanwan Zheng <teiwanwan at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: libarmadillo: apt-get install -y libarmadillo-dev (deb), libblas: apt-get install -y libblas-dev (deb), liblapack: apt-get install -y liblapack-dev (deb), libarpack++2: apt-get install -y libarpack++2-dev (deb), gfortran: apt-get install -y gfortran (deb)
CRAN checks: fmf results

Downloads:

Reference manual: fmf.pdf
Package source: fmf_1.1.1.tar.gz
Windows binaries: r-devel: fmf_1.1.1.zip, r-devel-UCRT: fmf_1.1.1.zip, r-release: fmf_1.1.1.zip, r-oldrel: fmf_1.1.1.zip
macOS binaries: r-release: fmf_1.1.1.tgz, r-oldrel: fmf_1.1.1.tgz

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