# Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)

## Documentation for package ‘randomForestSRC’ version 3.3.3

- DESCRIPTION file.
- Package NEWS.

## Help Pages

randomForestSRC-package | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
breast | Wisconsin Prognostic Breast Cancer Data
extract.bootsample | Subsample Forests for VIMP Confidence Intervals
extract.quantile | Quantile Regression Forests
extract.subsample | Subsample Forests for VIMP Confidence Intervals
find.interaction | Find Interactions Between Pairs of Variables
find.interaction.rfsrc | Find Interactions Between Pairs of Variables
follic | Follicular Cell Lymphoma
get.auc | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.bayes.rule | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.brier.error | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.brier.survival | Plot of Survival Estimates
get.cindex | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.confusion | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.imbalanced.optimize | Imbalanced Two Class Problems
get.imbalanced.performance | Imbalanced Two Class Problems
get.logloss | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.misclass.error | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.cserror | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.csvimp | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.error | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.error.block | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.formula | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.predicted | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.mv.vimp | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
get.partial.plot.data | Acquire Partial Effect of a Variable
get.pr.auc | Imbalanced Two Class Problems
get.pr.curve | Imbalanced Two Class Problems
get.quantile | Quantile Regression Forests
get.quantile.crps | Quantile Regression Forests
get.quantile.stat | Quantile Regression Forests
get.rfq.threshold | Imbalanced Two Class Problems
get.tree | Extract a Single Tree from a Forest and plot it on your browser
get.tree.rfsrc | Extract a Single Tree from a Forest and plot it on your browser
hd | Hodgkin's Disease
holdout.vimp | Hold out variable importance (VIMP)
holdout.vimp.rfsrc | Hold out variable importance (VIMP)
housing | Ames Iowa Housing Data
imbalanced | Imbalanced Two Class Problems
imbalanced.rfsrc | Imbalanced Two Class Problems
impute | Impute Only Mode
impute.rfsrc | Impute Only Mode
max.subtree | Acquire Maximal Subtree Information
max.subtree.rfsrc | Acquire Maximal Subtree Information
nutrigenomic | Nutrigenomic Study
partial | Acquire Partial Effect of a Variable
partial.rfsrc | Acquire Partial Effect of a Variable
pbc | Primary Biliary Cirrhosis (PBC) Data
peakVO2 | Systolic Heart Failure Data
plot.competing.risk | Plots for Competing Risks
plot.competing.risk.rfsrc | Plots for Competing Risks
plot.quantreg | Plot Quantiles from Quantile Regression Forests
plot.quantreg.rfsrc | Plot Quantiles from Quantile Regression Forests
plot.rfsrc | Plot Error Rate and Variable Importance from a RF-SRC analysis
plot.subsample | Plot Subsampled VIMP Confidence Intervals
plot.subsample.rfsrc | Plot Subsampled VIMP Confidence Intervals
plot.survival | Plot of Survival Estimates
plot.survival.rfsrc | Plot of Survival Estimates
plot.variable | Plot Marginal Effect of Variables
plot.variable.rfsrc | Plot Marginal Effect of Variables
predict.rfsrc | Prediction for Random Forests for Survival, Regression, and Classification
print.bootsample | Subsample Forests for VIMP Confidence Intervals
print.bootsample.rfsrc | Subsample Forests for VIMP Confidence Intervals
print.rfsrc | Print Summary Output of a RF-SRC Analysis
print.subsample | Subsample Forests for VIMP Confidence Intervals
print.subsample.rfsrc | Subsample Forests for VIMP Confidence Intervals
quantreg | Quantile Regression Forests
quantreg.rfsrc | Quantile Regression Forests
randomForestSRC | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
rfsrc | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
rfsrc.anonymous | Anonymous Random Forests
rfsrc.cart | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
rfsrc.fast | Fast Random Forests
rfsrc.news | Show the NEWS file
sid.perf.metric | sidClustering using SID (Staggered Interaction Data) for Unsupervised Clustering
sidClustering | sidClustering using SID (Staggered Interaction Data) for Unsupervised Clustering
sidClustering.rfsrc | sidClustering using SID (Staggered Interaction Data) for Unsupervised Clustering
stat.split | Acquire Split Statistic Information
stat.split.rfsrc | Acquire Split Statistic Information
subsample | Subsample Forests for VIMP Confidence Intervals
subsample.rfsrc | Subsample Forests for VIMP Confidence Intervals
synthetic | Synthetic Random Forests
synthetic.rfsrc | Synthetic Random Forests
tune | Tune Random Forest for the optimal mtry and nodesize parameters
tune.nodesize | Tune Random Forest for the optimal mtry and nodesize parameters
tune.nodesize.rfsrc | Tune Random Forest for the optimal mtry and nodesize parameters
tune.rfsrc | Tune Random Forest for the optimal mtry and nodesize parameters
var.select | Variable Selection
var.select.rfsrc | Variable Selection
vdv | van de Vijver Microarray Breast Cancer
veteran | Veteran's Administration Lung Cancer Trial
vimp | VIMP for Single or Grouped Variables
vimp.rfsrc | VIMP for Single or Grouped Variables
wihs | Women's Interagency HIV Study (WIHS)
wine | White Wine Quality Data