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PLORN  

Prediction with Less Overfitting and Robust to Noise
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PLORN", "0.1.1")



Attach the package and use:
library("PLORN")
Maintained by
Takahiko Koizumi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-03-21
Latest Update: 2022-03-21
Description:
A method for the quantitative prediction with much predictors. This package provides functions to construct the quantitative prediction model with less overfitting and robust to noise.
How to cite:
Takahiko Koizumi (2022). PLORN: Prediction with Less Overfitting and Robust to Noise. R package version 0.1.1, https://cran.r-project.org/web/packages/PLORN. Accessed 05 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited PLORN R package
View PLORN citation profile
Other R packages that PLORN depends, imports, suggests or enhances
Complete documentation for PLORN
Functions, R codes and Examples using the PLORN R package
Some associated functions: Pinus . p.clean . p.opt . p.pca . p.rank . p.sort . plorn . 
Some associated R codes: p.clean.R . p.opt.R . p.pca.R . p.rank.R . p.sort.R . plorn.R .  Full PLORN package functions and examples
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