Package index • ggRandomForests

Forest Objects

Extract and display data from random forest objects.

Visualize forest convergence and training error.

Assess and plot variable importance (VIMP).

gg_vimp(): Variable Importance (VIMP) data object
plot(<gg_vimp>): Plot a gg_vimp object, extracted variable importance of a rfsrc object
gg_varpro(): Variable importance data from a varPro model
plot(<gg_varpro>): Plot a gg_varpro variable importance object
gg_beta_varpro(): Per-variable lasso-beta importance from a varPro fit
plot(<gg_beta_varpro>): Plot a gg_beta_varpro object
gg_udependent(): Variable dependency graph from a uvarpro model
plot(<gg_udependent>): Plot a gg_udependent variable dependency graph
gg_ivarpro(): Individual (local) variable importance from a varPro fit
plot(<gg_ivarpro>): Plot a gg_ivarpro object

Score and plot per-observation anomaly scores.

Marginal variable dependence plots.

Partial dependence plots for individual variables.

gg_partial(): Split partial dependence data into continuous or categorical datasets
plot(<gg_partial>): Plot a gg_partial object
gg_partial_rfsrc(): Partial dependence data from an rfsrc model
plot(<gg_partial_rfsrc>): Plot a gg_partial_rfsrc object
gg_partial_varpro() gg_partialpro(): Partial dependence data from a varPro model
plot(<gg_partialpro>) plot(<gg_partial_varpro>): Plot a gg_partial_varpro object

Survival curves, ROC, and related diagnostics.

gg_survival(): Nonparametric survival estimates.
plot(<gg_survival>): Plot a gg_survival object.
gg_roc(<rfsrc>): ROC (Receiver Operating Characteristic) curve data from a classification forest.
plot(<gg_roc>): ROC plot generic function for a gg_roc object.
calc_roc(<rfsrc>): Receiver Operator Characteristic calculator
calc_auc(): Area Under the ROC Curve calculator
surv_partial.rfsrc(): Survival partial dependence data for one or more predictors
kaplan(): nonparametric Kaplan-Meier estimates
nelson(): nonparametric Nelson-Aalen estimates
gg_brier(): Brier score and CRPS for survival forests
plot(<gg_brier>): Plot a gg_brier object

Standard R generics implemented for all gg_* data objects.

autoplot(<gg_error>) autoplot(<gg_vimp>) autoplot(<gg_rfsrc>) autoplot(<gg_variable>) autoplot(<gg_partial>) autoplot(<gg_partial_rfsrc>) autoplot(<gg_partialpro>) autoplot(<gg_partial_varpro>) autoplot(<gg_roc>) autoplot(<gg_survival>) autoplot(<gg_brier>) autoplot(<gg_varpro>) autoplot(<gg_udependent>) autoplot(<gg_isopro>): autoplot methods for ggRandomForests data objects
print(<gg_error>) print(<gg_vimp>) print(<gg_rfsrc>) print(<gg_variable>) print(<gg_partial>) print(<gg_partial_rfsrc>) print(<gg_partialpro>) print(<gg_partial_varpro>) print(<gg_roc>) print(<gg_survival>) print(<gg_brier>) print(<gg_udependent>) print(<summary.gg_udependent>) print(<gg_varpro>) print(<gg_isopro>) print(<gg_beta_varpro>) print(<gg_ivarpro>): Print methods for gg_* data objects
print(<summary.gg>) summary(<gg_error>) summary(<gg_vimp>) summary(<gg_rfsrc>) summary(<gg_variable>) summary(<gg_partial>) summary(<gg_partial_rfsrc>) summary(<gg_partialpro>) summary(<gg_partial_varpro>) summary(<gg_roc>) summary(<gg_survival>) summary(<gg_varpro>) summary(<gg_udependent>) summary(<gg_brier>) summary(<gg_isopro>) summary(<gg_beta_varpro>) summary(<gg_ivarpro>): Summary methods for gg_* data objects

Helper functions used internally and by users.

quantile_pts(): Quantile-based cut points for coplots
varpro_feature_names(): Recover original variable names from varpro one-hot encoded feature names

ggRandomForests-package: ggRandomForests: Visually Exploring Random Forests