Fast Unified Random Forests for Survival, Regression, and
Classification (RF-SRC)
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Documentation for package ‘randomForestSRC’ version 3.8.0
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B C E F G H I L M N P Q R S T V W
| randomForestSRC-package | Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC) |
-- B --
| breast | Wisconsin Prognostic Breast Cancer Data |
-- C --
| classification.performance | Classification Performance Metrics |
-- E --
| extract.bootsample | Subsampling Inference for Variable Importance and Prediction Error |
| extract.quantile | Quantile Regression Forests |
| extract.subsample | Subsampling Inference for Variable Importance and Prediction Error |
-- F --
| fast.load | Fast Saving and Loading Objects |
| fast.load.list | Fast Saving and Loading Objects |
| fast.save | Fast Saving and Loading Objects |
| fast.save.list | Fast Saving and Loading Objects |
| fast.saveload | Fast Saving and Loading Objects |
| follic | Follicular Cell Lymphoma |
-- G --
| get.auc | Classification Performance Metrics |
| get.auct.survival | Survival Prediction Performance and Diagnostic Plots |
| get.bayes.rule | Classification Performance Metrics |
| get.brier.error | Classification Performance Metrics |
| get.brier.survival | Survival Prediction Performance and Diagnostic Plots |
| get.cindex | Survival Prediction Performance and Diagnostic Plots |
| get.confusion | Classification Performance Metrics |
| get.imbalanced.optimize | Random Forests for Imbalanced Two-Class Classification |
| get.imbalanced.performance | Random Forests for Imbalanced Two-Class Classification |
| get.logloss | Classification Performance Metrics |
| get.misclass.error | Classification Performance Metrics |
| get.mv.cserror | Extracting Multivariate Values |
| get.mv.csvimp | Extracting Multivariate Values |
| get.mv.error | Extracting Multivariate Values |
| get.mv.error.block | Extracting Multivariate Values |
| get.mv.formula | Extracting Multivariate Values |
| get.mv.predicted | Extracting Multivariate Values |
| get.mv.vimp | Extracting Multivariate Values |
| get.partial.plot.data | Compute Partial Dependence Values |
| get.pinball.error | Quantile Regression Forests |
| get.pr.auc | Classification Performance Metrics |
| get.pr.curve | Classification Performance Metrics |
| get.quantile | Quantile Regression Forests |
| get.quantile.crps | Quantile Regression Forests |
| get.quantile.stat | Quantile Regression Forests |
| get.rfq.threshold | Random Forests for Imbalanced Two-Class Classification |
| 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 |
-- H --
| hd | Hodgkin's Disease |
| holdout.vimp | Hold out variable importance (VIMP) |
| holdout.vimp.rfsrc | Hold out variable importance (VIMP) |
| housing | Ames Iowa Housing Data |
-- I --
| imbalanced | Random Forests for Imbalanced Two-Class Classification |
| imbalanced.rfsrc | Random Forests for Imbalanced Two-Class Classification |
| impute | Impute Only Mode |
| impute.learn | Learn a predictive imputer for test-time imputation and OOD scoring |
| impute.learn.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
| impute.ood | Learn a predictive imputer for test-time imputation and OOD scoring |
| impute.ood.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
| impute.rfsrc | Impute Only Mode |
-- L --
| load.impute.learn | Learn a predictive imputer for test-time imputation and OOD scoring |
| load.impute.learn.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
-- M --
| max.subtree | Acquire Maximal Subtree Information |
| max.subtree.rfsrc | Acquire Maximal Subtree Information |
| multivariate.values | Extracting Multivariate Values |
-- N --
| nutrigenomic | Nutrigenomic Study |
-- P --
| partial | Compute Partial Dependence Values |
| partial.rfsrc | Compute Partial Dependence Values |
| 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 Conditional Quantiles and CRPS Diagnostics |
| plot.quantreg.rfsrc | Plot Conditional Quantiles and CRPS Diagnostics |
| plot.rfsrc | Plot Error Rate and Variable Importance from a RF-SRC analysis |
| plot.subsample | Plot Subsampling Confidence Intervals for Variable Importance |
| plot.subsample.rfsrc | Plot Subsampling Confidence Intervals for Variable Importance |
| plot.survival | Survival Prediction Performance and Diagnostic Plots |
| plot.survival.rfsrc | Survival Prediction Performance and Diagnostic Plots |
| plot.variable | Plot Marginal and Partial Dependence of Predictors |
| plot.variable.rfsrc | Plot Marginal and Partial Dependence of Predictors |
| plotBrierAUC | Survival Prediction Performance and Diagnostic Plots |
| predict.impute.learn | Learn a predictive imputer for test-time imputation and OOD scoring |
| predict.impute.learn.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
| predict.rfsrc | Prediction for Random Forests for Survival, Regression, and Classification |
| print.bootsample | Subsampling Inference for Variable Importance and Prediction Error |
| print.bootsample.rfsrc | Subsampling Inference for Variable Importance and Prediction Error |
| print.imbalanced.performance | Random Forests for Imbalanced Two-Class Classification |
| print.impute.learn | Learn a predictive imputer for test-time imputation and OOD scoring |
| print.impute.learn.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
| print.rfsrc | Print Summary Output of a RF-SRC Analysis |
| print.subsample | Subsampling Inference for Variable Importance and Prediction Error |
| print.subsample.rfsrc | Subsampling Inference for Variable Importance and Prediction Error |
-- Q --
| quantreg | Quantile Regression Forests |
| quantreg.rfsrc | Quantile Regression Forests |
-- R --
| 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 |
-- S --
| save.impute.learn | Learn a predictive imputer for test-time imputation and OOD scoring |
| save.impute.learn.rfsrc | Learn a predictive imputer for test-time imputation and OOD scoring |
| 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 |
| subsample | Subsampling Inference for Variable Importance and Prediction Error |
| subsample.rfsrc | Subsampling Inference for Variable Importance and Prediction Error |
-- T --
| tune | Tune Random Forest for optimal 'mtry' and 'nodesize' |
| tune.nodesize | Tune Random Forest for optimal 'mtry' and 'nodesize' |
| tune.nodesize.rfsrc | Tune Random Forest for optimal 'mtry' and 'nodesize' |
| tune.rfsrc | Tune Random Forest for optimal 'mtry' and 'nodesize' |
-- V --
| 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 |
-- W --
| wihs | Women's Interagency HIV Study (WIHS) |
| wine | White Wine Quality Data |