CRAN/E | rgnoisefilt

rgnoisefilt

Elimination of Noisy Samples in Regression Datasets using Noise Filters

Installation

About

Traditional noise filtering methods aim at removing noisy samples from a classification dataset. This package adapts classic and recent filtering techniques for use in regression problems, and it also incorporates methods specifically designed for regression data. In order to do this, it uses approaches proposed in the specialized literature, such as Martin et al. (2021) [doi:10.1109/ACCESS.2021.3123151] and Arnaiz-Gonzalez et al. (2016) [doi:10.1016/j.eswa.2015.12.046]. Thus, the goal of the implemented noise filters is to eliminate samples with noise in regression datasets.

github.com/juanmartinsantos/rgnoisefilt
Copyright see file COPYRIGHTS

Key Metrics

Version 1.1.2
R ≥ 3.2.0
Published 2023-10-02 212 days ago
Needs compilation? no
License GPL (≥ 3)
CRAN checks rgnoisefilt results

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Maintainer

Maintainer

Juan Martin

juanmartin@usal.es

Authors

Juan Martin

aut / cre

José A. Sáez

aut

Emilio Corchado

aut

Pablo Morales

ctb

(Author of the NoiseFiltersR package)

Julian Luengo

ctb

(Author of the NoiseFiltersR package)

Luis P.F. Garcia

ctb

(Author of the NoiseFiltersR package)

Ana C. Lorena

ctb

(Author of the NoiseFiltersR package)

Andre C.P.L.F. de Carvalho

ctb

(Author of the NoiseFiltersR package)

Francisco Herrera

ctb

(Author of the NoiseFiltersR package)

Material

NEWS
Reference manual
Package source

Vignettes

rgnoisefilt

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

rgnoisefilt archive

Depends

R ≥ 3.2.0

Imports

e1071
FNN
gbm
modelr
nnet
randomForest
rpart
arules
infotheo
entropy
ggplot2
class
kknn

Suggests

testthat ≥ 3.0.0
knitr
rmarkdown