rgnoisefilt
1.1.3Elimination of Noisy Samples in Regression Datasets using Noise Filters
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 88%
Downloads
Repository
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Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1.3Latest
- unarchivedReturned to CRAN2025-05-23
- archivedRemoved from CRAN2025-05-15requires archived package 'kknn'
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.1.22023-10-02 · diff ↗
- 1.1.12023-09-13
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-09-13
- Total releases
- 3 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 3.2.0
- Download size
- 64 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet