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Dforest  

Decision Forest
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("Dforest", "0.4.2")



Attach the package and use:
library("Dforest")
Maintained by
Leihong Wu
[Scholar Profile | Author Map]
First Published: 2017-06-26
Latest Update: 2017-11-28
Description:
Provides R-implementation of Decision forest algorithm, which combines the predictions of multiple independent decision tree models for a consensus decision. In particular, Decision Forest is a novel pattern-recognition method which can be used to analyze: (1) DNA microarray data; (2) Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) data; and (3) Structure-Activity Relation (SAR) data. In this package, three fundamental functions are provided, as (1)DF_train, (2)DF_pred, and (3)DF_CV. run Dforest() to see more instructions. Weida Tong (2003) .
How to cite:
Leihong Wu (2017). Dforest: Decision Forest. R package version 0.4.2, https://cran.r-project.org/web/packages/Dforest. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.4.0 (2017-06-26 16:03)
Other packages that cited Dforest R package
View Dforest citation profile
Other R packages that Dforest depends, imports, suggests or enhances
Complete documentation for Dforest
Functions, R codes and Examples using the Dforest R package
Some associated functions: Con_DT . DF_CV . DF_CVsummary . DF_ConfPlot . DF_ConfPlot_accu . DF_Trainsummary . DF_acc . DF_calp . DF_dataFs . DF_dataPre . DF_easy . DF_perf . DF_pred . DF_train . Dforest . Pred_DT . cal_MCC . data_dili . multiplot . 
Some associated R codes: DF_CV.R . DF_CV_plot.R . DF_ConfPlot.R . DF_dataFs.R . DF_dataPre.R . DF_easy.R . DF_pred.R . DF_train.R . DForest.R . DT_con.R .  Full Dforest package functions and examples
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