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ordinalForest  

Ordinal Forests: Prediction and Variable Ranking with Ordinal Target Variables
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ordinalForest", "2.4-4")



Attach the package and use:
library("ordinalForest")
Maintained by
Roman Hornung
[Scholar Profile | Author Map]
First Published: 2017-04-13
Latest Update: 2022-11-30
Description:
The ordinal forest (OF) method allows ordinal regression with high-dimensional and low-dimensional data. After having constructed an OF prediction rule using a training dataset, it can be used to predict the values of the ordinal target variable for new observations. Moreover, by means of the (permutation-based) variable importance measure of OF, it is also possible to rank the covariates with respect to their importance in the prediction of the values of the ordinal target variable. OF is presented in Hornung (2020). NOTE: Starting with package version 2.4, it is also possible to obtain class probability predictions in addition to the class point predictions. Moreover, the variable importance values can also be based on the class probability predictions. Preliminary results indicate that this might lead to a better discrimination between influential and non-influential covariates. The main functions of the package are: ordfor() (construction of OF) and predict.ordfor() (prediction of the target variable values of new observations). References: Hornung R. (2020) Ordinal Forests. Journal of Classification 37, 4
How to cite:
Roman Hornung (2017). ordinalForest: Ordinal Forests: Prediction and Variable Ranking with Ordinal Target Variables. R package version 2.4-4, https://cran.r-project.org/web/packages/ordinalForest. Accessed 03 May. 2025.
Previous versions and publish date:
1.0 (2017-04-13 23:00), 2.0 (2017-07-26 19:21), 2.1 (2017-10-20 20:18), 2.2 (2018-07-16 17:20), 2.3-1 (2019-02-06 12:20), 2.3 (2019-01-24 13:50), 2.4-1 (2020-07-22 23:10), 2.4-2 (2021-06-25 15:30), 2.4-3 (2022-11-30 14:50), 2.4 (2020-07-13 19:40)
Other packages that cited ordinalForest R package
View ordinalForest citation profile
Other R packages that ordinalForest depends, imports, suggests or enhances
Complete documentation for ordinalForest
Functions, R codes and Examples using the ordinalForest R package
Some associated functions: hearth . ordfor . ordinalForest-package . perff . predict.ordfor . 
Some associated R codes: RcppExports.R . hearth.R . ordfor.R . ordinalForest-package.R . perff.R . predict.R . predict.ordfor.R . print.ordfor.R . print.ordforpred.R . rangerordfor.R . simulateborders.R . youdenindex.R .  Full ordinalForest package functions and examples
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