Package: Dforest 0.4.2

Dforest: Decision Forest

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) <doi:10.1021/ci020058s>.

Authors:Leihong Wu <[email protected]>, Weida Tong

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Dforest/json (API)

# Install 'Dforest' in R:

install.packages('Dforest', repos = c('https://lhnctr.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

data_dili - QSAR dataset with DILI endpoint for demo

On CRAN:

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

1.00 score 8 scripts 183 downloads 16 exports 29 dependencies

Last updated 7 years agofrom:729bce9030. Checks:8 OK. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Mar 02 2025
R-4.5-win	OK	Mar 02 2025
R-4.5-mac	OK	Mar 02 2025
R-4.5-linux	OK	Mar 02 2025
R-4.4-win	OK	Mar 02 2025
R-4.4-mac	OK	Mar 02 2025
R-4.3-win	OK	Mar 02 2025
R-4.3-mac	OK	Mar 02 2025

Exports:cal_MCC Con_DT DF_acc DF_ConfPlot DF_ConfPlot_accu DF_CV DF_CVsummary DF_dataFs DF_dataPre DF_easy DF_perf DF_pred DF_train DF_Trainsummary Dforest Pred_DT

Dependencies:cli colorspace fansi farver ggplot2 glue gtable isoband labeling lattice lifecycle magrittr MASS Matrix mgcv munsell nlme pillar pkgconfig R6 RColorBrewer rlang rpart scales tibble utf8 vctrs viridisLite withr

Help page	Topics
Performance evaluation from other modeling algorithm Result	cal_MCC
Construct Decision Tree model with pruning	Con_DT
QSAR dataset with DILI endpoint for demo	data_dili
Performance evaluation from Decision Tree Predictions	DF_acc
T-test for feature selection	DF_calp
Decision Forest algorithm: confidence level accumulated plot	DF_ConfPlot
Decision Forest algorithm: confidence level accumulated plot (accumulated version)	DF_ConfPlot_accu
Decision Forest algorithm: Model training with Cross-validation	DF_CV
output summary for Dforest Cross-validation results	DF_CVsummary
Decision Forest algorithm: Feature Selection in pre-processing	DF_dataFs
Decision Forest algorithm: Data pre-processing	DF_dataPre
Simple pre-defined pipeline for Decision forest	DF_easy
performance evaluation between two factors	DF_perf
Decision Forest algorithm: Model prediction	DF_pred
Decision Forest algorithm: Model training	DF_train
output summary for Dforest test results	DF_Trainsummary
Demo script to lean Decision Forest package Demo data are located in data/ folder	Dforest
multiplot	multiplot
Doing Prediction with Decision Tree model	Pred_DT

Package: Dforest 0.4.2

Dforest: Decision Forest

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)