This package is considered a duplicate. The official version of this package is found at:https://zheng-ww.r-universe.dev/fmf

Package: fmf 1.1.1

Wanwan Zheng

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.

Authors:Wanwan Zheng [aut, cre], Mingzhe Jin [aut], Lampros Mouselimis [ctb, cph]

fmf_1.1.1.tar.gz
fmf_1.1.1.tar.gz(r-4.5-noble)fmf_1.1.1.tar.gz(r-4.4-noble)
fmf_1.1.1.tgz(r-4.4-emscripten)fmf_1.1.1.tgz(r-4.3-emscripten)
fmf.pdf |fmf.html✨
fmf/json (API)

# Install 'fmf' in R:

install.packages('fmf', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

australian - Australian Credit Approval
iris - Iris Data Set
ozone - Ozone Level Detection Data Set

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp openmp

1.00 score 1 scripts 115 downloads 4 exports 154 dependencies

Last updated 4 years agofrom:2f4f71ce05. Checks:OK: 1 NOTE: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 10 2024
R-4.5-linux-x86_64	NOTE	Dec 10 2024

Exports:fmf normalization plot tuning

Dependencies:abind backports base64enc boot broom bslib C50 cachem car carData caret class cli clock cluster codetools colorspace corrplot cowplot cpp11 crosstalk Cubist data.table dendextend Deriv diagram digest doBy dplyr DT e1071 ellipse emmeans estimability evaluate factoextra FactoMineR fansi farver fastmap flashClust fontawesome foreach Formula fs future future.apply generics ggplot2 ggpubr ggrepel ggsci ggsignif globals glue gower gridExtra gtable hardhat highr htmltools htmlwidgets httpuv igraph inum ipred isoband iterators jquerylib jsonlite kernlab KernSmooth knitr labeling later lattice lava lazyeval leaps lgr libcoin lifecycle listenv lme4 lubridate magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa ModelMetrics modelr multcompView munsell mvtnorm nlme nloptr nnet numDeriv parallelly partykit pbkrtest pillar pkgconfig plyr polynom pROC prodlim progressr promises proxy purrr quantreg R6 ranger rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen recipes reshape2 rlang rmarkdown rpart rstatix sass scales scatterplot3d shape solitude SparseM SQUAREM stringi stringr survival tibble tidyr tidyselect timechange timeDate tinytex tzdb utf8 vctrs viridis viridisLite withr xfun yaml

Citation

Readme and manuals

Help Manual

Help page	Topics
Australian Credit Approval	australian
Fast Class Noise Detector with Multi-Factor-Based Learning	fmf fmf.default fmf.formula
Iris Data Set	iris
The Max-Min Normalization	normalization
Ozone Level Detection Data Set	ozone
PCA Plot of the Noise Score of Each Individual	plot
Tuning For Fast Class Noise Detector with Multi-Factor-Based Learning	tuning tuning.default tuning.formula

Package: fmf 1.1.1

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

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)