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fmf  

Fast Class Noise Detector with Multi-Factor-Based Learning
View on CRAN: Click here


Download and install fmf package within the R console
Install from CRAN:
install.packages("fmf")

Install from Github:
library("remotes")
install_github("cran/fmf")

Install by package version:
library("remotes")
install_version("fmf", "1.1.1")



Attach the package and use:
library("fmf")
Maintained by
Wanwan Zheng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-03
Latest Update: 2020-09-03
Description:
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.
How to cite:
Wanwan Zheng (2020). fmf: Fast Class Noise Detector with Multi-Factor-Based Learning. R package version 1.1.1, https://cran.r-project.org/web/packages/fmf. Accessed 22 Dec. 2024.
Previous versions and publish date:
No previous versions
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View fmf citation profile
Other R packages that fmf depends, imports, suggests or enhances
Complete documentation for fmf
Functions, R codes and Examples using the fmf R package
Some associated functions: FUNCTION_weights . australian . class_folds . entropy . fmf . func_categorical_preds . func_shuffle . func_tbl . func_tbl_dist . iris . kernelknn . normalization . normalized . ozone . plot . regr_folds . switch.ops . tuning . 
Some associated R codes: RcppExports.R . fmf.R . kernelknn.R . normalization.R . package.R . plot.R . tuning.R . utils.R .  Full fmf package functions and examples
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