rgnoisefilt
Elimination of Noisy Samples in Regression Datasets using Noise Filters
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.
- Version1.1.2
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release10/02/2023
Documentation
Team
- Juan Martin
- José A. SáezShow author detailsRolesAuthor
- Francisco HerreraShow author detailsRolesContributor
- Emilio CorchadoShow author detailsRolesAuthor
- Pablo MoralesShow author detailsRolesContributor
- Julian LuengoShow author detailsRolesContributor
- Luis P.F. GarciaShow author detailsRolesContributor
- Ana C. LorenaShow author detailsRolesContributor
- Andre C.P.L.F. de CarvalhoShow author detailsRolesContributor
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- Imports13 packages
- Suggests3 packages