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forestError  

A Unified Framework for Random Forest Prediction Error Estimation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("forestError", "1.1.0")



Attach the package and use:
library("forestError")
Maintained by
Benjamin Lu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-14
Latest Update: 2021-08-10
Description:
Estimates the conditional error distributions of random forest predictions and common parameters of those distributions, including conditional misclassification rates, conditional mean squared prediction errors, conditional biases, and conditional quantiles, by out-of-bag weighting of out-of-bag prediction errors as proposed by Lu and Hardin (2021). This package is compatible with several existing packages that implement random forests in R.
How to cite:
Benjamin Lu (2020). forestError: A Unified Framework for Random Forest Prediction Error Estimation. R package version 1.1.0, https://cran.r-project.org/web/packages/forestError
Previous versions and publish date:
0.1.0 (2020-01-14 12:30), 0.1.1 (2020-01-31 06:50), 0.2.0 (2020-04-02 07:50), 1.0.0 (2021-02-11 21:20)
Other packages that cited forestError R package
View forestError citation profile
Other R packages that forestError depends, imports, suggests or enhances
Functions, R codes and Examples using the forestError R package
Some associated functions: estimateErrorParams . findOOBErrors . findTestPreds . perror . qerror . quantForestError . 
Some associated R codes: checkargs.R . estimateerrorparams.R . findooberrors.R . findtestpreds.R . perror.R . qerror.R . quantforesterror.R .  Full forestError package functions and examples
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