Package: evreg 1.1.1

Thierry Denoeux

evreg: Evidential Regression

An implementation of the 'Evidential Neural Network for Regression' model recently introduced in Denoeux (2023) <doi:10.1109/TFUZZ.2023.3268200>. In this model, prediction uncertainty is quantified by Gaussian random fuzzy numbers as introduced in Denoeux (2023) <doi:10.1016/j.fss.2022.06.004>. The package contains functions for training the network, tuning hyperparameters by cross-validation or the hold-out method, and making predictions. It also contains utilities for making calculations with Gaussian random fuzzy numbers (such as, e.g., computing the degrees of belief and plausibility of an interval, or combining Gaussian random fuzzy numbers).

Authors:Thierry Denoeux [aut, cre]

evreg_1.1.1.tar.gz
evreg_1.1.1.tar.gz(r-4.5-noble)evreg_1.1.1.tar.gz(r-4.4-noble)
evreg_1.1.1.tgz(r-4.4-emscripten)evreg_1.1.1.tgz(r-4.3-emscripten)
evreg.pdf |evreg.html
evreg/json (API)
NEWS

# Install 'evreg' in R:
install.packages('evreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.48 score 2 scripts 290 downloads 10 exports 14 dependencies

Last updated 6 months agofrom:deb26b44aa. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-linuxOKNov 06 2024

Exports:BelBelintcombination_GRFNENNregENNreg_cvENNreg_holdoutENNreg_initintervalsPlpl_contour

Dependencies:evclustFNNlatticelimSolvelpSolveMASSMatrixmclustplyrquadprogR.methodsS3R.ooR.utilsRcpp

Introduction to the evreg package

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-05-09
Started: 2023-01-17