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noisemodel  

Noise Models for Classification Datasets
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("noisemodel", "1.0.2")



Attach the package and use:
library("noisemodel")
Maintained by
José A. Sáez
[Scholar Profile | Author Map]
First Published: 2022-10-17
Latest Update: 2022-10-17
Description:
Implementation of models for the controlled introduction of errors in classification datasets. This package contains the noise models described in Saez (2022) that allow corrupting class labels, attributes and both simultaneously.
How to cite:
José A. Sáez (2022). noisemodel: Noise Models for Classification Datasets. R package version 1.0.2, https://cran.r-project.org/web/packages/noisemodel. Accessed 13 May. 2025.
Previous versions and publish date:
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Other R packages that noisemodel depends, imports, suggests or enhances
Complete documentation for noisemodel
Functions, R codes and Examples using the noisemodel R package
Some associated functions: asy_def_ln . asy_int_an . asy_spa_ln . asy_uni_an . asy_uni_ln . attm_uni_ln . bord_dist . bord_noise . boud_gau_an . clu_vot_ln . diris2D . exp_bor_ln . exps_cuni_ln . findnoise . fra_bdir_ln . gam_bor_ln . gau_bor_ln . gaum_bor_ln . glev_uni_ln . hubp_uni_ln . imp_int_an . iris2D . irs_bdir_ln . lap_bor_ln . larm_uni_ln . maj_udir_ln . mind_bdir_ln . minp_uni_ln . mis_pre_ln . mulc_udir_ln . nei_bor_ln . nlin_bor_ln . noisetype . oned_uni_ln . opes_idnn_ln . opes_idu_ln . pai_bdir_ln . plot.ndmodel . pmd_con_ln . print.ndmodel . print.sum.ndmodel . qua_uni_ln . runif_replace . safe_sample . sample_replace . sco_con_ln . sigb_uni_ln . smam_bor_ln . smu_cuni_ln . summary.ndmodel . sym_adj_ln . sym_cen_ln . sym_con_ln . sym_cuni_an . sym_cuni_cn . sym_cuni_ln . sym_ddef_ln . sym_def_ln . sym_dia_ln . sym_dran_ln . sym_end_an . sym_exc_ln . sym_gau_an . sym_hie_ln . sym_hienc_ln . sym_int_an . sym_natd_ln . sym_nean_ln . sym_nexc_ln . sym_nuni_ln . sym_opt_ln . sym_pes_ln . sym_sgau_an . sym_uni_an . sym_uni_ln . sym_usim_ln . symd_gau_an . symd_gimg_an . symd_rpix_an . symd_uni_an . ugau_bor_ln . ulap_bor_ln . unc_fixw_an . unc_vgau_an . uncs_guni_cn . 
Some associated R codes: 000_common.R . 001_asy_def_ln.R . 002_asy_spa_ln.R . 003_asy_uni_ln.R . 004_attm_uni_ln.R . 005_clu_vot_ln.R . 006_exp_bor_ln.R . 007_exps_cuni_ln.R . 008_fra_bdir_ln.R . 009_gam_bor_ln.R . 010_gau_bor_ln.R . 011_glev_uni_ln.R . 012_gaum_bor_ln.R . 013_hubp_uni_ln.R . 014_irs_bdir_ln.R . 015_lap_bor_ln.R . 016_larm_uni_ln.R . 017_maj_udir_ln.R . 018_mind_bdir_ln.R . 019_minp_uni_ln.R . 020_mis_pre_ln.R . 021_mulc_udir_ln.R . 022_nei_bor_ln.R . 023_nlin_bor_ln.R . 024_oned_uni_ln.R . 025_opes_idnn_ln.R . 026_opes_idu_ln.R . 027_pai_bdir_ln.R . 028_pmd_con_ln.R . 029_qua_uni_ln.R . 030_sco_con_ln.R . 031_sigb_uni_ln.R . 032_smam_bor_ln.R . 033_smu_cuni_ln.R . 034_sym_adj_ln.R . 035_sym_cen_ln.R . 036_sym_cuni_ln.R . 037_sym_con_ln.R . 038_sym_def_ln.R . 039_sym_dia_ln.R . 040_sym_ddef_ln.R . 041_sym_dran_ln.R . 042_sym_exc_ln.R . 043_sym_hie_ln.R . 044_sym_hienc_ln.R . 045_sym_natd_ln.R . 046_sym_nean_ln.R . 047_sym_nexc_ln.R . 048_sym_nuni_ln.R . 049_sym_opt_ln.R . 050_sym_pes_ln.R . 051_sym_uni_ln.R . 052_sym_usim_ln.R . 053_ugau_bor_ln.R . 054_ulap_bor_ln.R . 055_asy_int_an.R . 056_asy_uni_an.R . 057_boud_gau_an.R . 058_imp_int_an.R . 059_sym_cuni_an.R . 060_sym_end_an.R . 061_sym_gau_an.R . 062_sym_int_an.R . 063_sym_sgau_an.R . 064_sym_uni_an.R . 065_symd_gau_an.R . 066_symd_gimg_an.R . 067_symd_rpix_an.R . 068_symd_uni_an.R . 069_unc_fixw_an.R . 070_unc_vgau_an.R . 071_sym_cuni_cn.R . 072_uncs_guni_cn.R . diris2D.R . iris2D.R . ndmodel.R .  Full noisemodel package functions and examples
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