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ggRandomForests (version 1.2.1)

Visually Exploring Random Forests

Description

Graphic elements for exploring Random Forests using the randomForestSRC package for survival, regression and classification forests and ggplot2 package plotting.

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Install

install.packages('ggRandomForests')

Monthly Downloads

749

Version

1.2.1

License

GPL (>= 3)

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Maintainer

John Ehrlinger

Last Published

December 12th, 2015

Functions in ggRandomForests (1.2.1)

calc_auc

Area Under the ROC Curve calculator
kaplan

nonparametric kaplan-meier estimates
gg_interaction

ggRandomForests-package

ggRandomForests: Visually Exploring Random Forests
gg_vimp.rfsrc

Variable Importance (VIMP) data object
gg_rfsrc.rfsrc

Predicted response data object
interaction_data

Cached find.interaction matrix objects for examples, diagnostics and vignettes. Data sets storing find.interaction matrix objects corresponding to training data according to the following naming convention:
  • interaction_iris- from a randomForestSR[C] for theirisdata set.
  • interaction_Boston- from a randomForestS[R]C for theBostonhousing data set (MASSpackage).
  • interaction_pbc- from a randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
quantile_pts

Find points evenly distributed along the vectors values.
gg_roc.rfsrc

ROC (Receiver operator curve) data from a classification random forest.
plot.gg_roc

plot.gg_interaction

plot.gg_vimp

Plot a gg_vimp object, extracted variable importance of a rfsrc object
combine.gg_partial

combine two gg_partial objects
gg_variable.rfsrc

Marginal variable depedance data object.
gg_error

randomForestSRC error rate data object
rfsrc_cache_datasets

Recreate the cached data sets for the ggRandomForests package
gg_minimal_vimp

Minimal depth vs VIMP camparison by variable rankings.
shift

lead function to shift by one (or more).
plot.gg_rfsrc

surface_matrix

Construct a set of (x, y, z) matrices for surface plotting a gg_partial_coplot object
gg_survival

Nonparametric survival estimates.
plot.gg_minimal_depth

Plot a gg_minimal_depth object for random forest variable ranking.
plot.gg_partial

calc_roc.rfsrc

Reciever Operator Characteristic calculator
gg_minimal_depth

Minimal depth data object ([randomForestSRC]{var.select})
rfsrc_data

Cached rfsrc objects for examples, diagnostics and vignettes. Data sets storing rfsrc objects corresponding to training data according to the following naming convention:
  • rfsrc_iris- randomForestSR[C] for theirisdata set.
  • rfsrc_Boston- randomForestS[R]C for theBostonhousing data set (MASSpackage).
  • rfsrc_pbc- randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
plot.gg_survival

partial.rfsrc

randomForestSRC partial dependence (data object) (modified from randomForestSRC V1.6.0)
partial_surface_data

Cached plot.variable objects for examples, diagnostics and vignettes. Data sets storing plot.variable objects corresponding to training data according to the following naming convention:
  • partial_Boston_surf- from a randomForestS[R]C for theBostonhousing data set (MASSpackage).
  • partial_pbc_surf- from a randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
  • partial_pbc_time- from a randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
gg_partial_coplot.rfsrc

Data structures for stratified partial coplots
plot.gg_error

partial_data

Cached plot.variable objects for examples, diagnostics and vignettes. Data sets storing plot.variable objects corresponding to training data according to the following naming convention:
  • partial_iris- from a randomForestSR[C] for theirisdata set.
  • partial_Boston- from a randomForestS[R]C for theBostonhousing data set (MASSpackage).
  • partial_pbc- from a randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
plot.gg_variable

gg_partial

Partial variable dependence object
plot.gg_partial_list

Partial variable dependence plot, operates on a gg_partial_list object.
logit_loess

logit_loess takes
partial_coplot_data

Cached plot.variable objects for examples, diagnostics and vignettes. Data sets storing rfsrc objects corresponding to training data according to the following naming convention:
  • partial_coplot_Boston- randomForestS[R]C for theBostonhousing data set (MASSpackage).
varsel_data

Cached var.select objects for examples, diagnostics and vignettes. Data sets storing var.select objects corresponding to training data according to the following naming convention:
  • varsel_iris- from a randomForestSR[C] for theirisdata set.
  • varsel_Boston- from a randomForestS[R]C for theBostonhousing data set (MASSpackage).
  • varsel_pbc- from a randomForest[S]RC for thepbcdata set (randomForestSRCpackage)
nelson

nonparametric Nelson-Aalen estimates
plot.gg_minimal_vimp

Plot a gg_minimal_vimp object for comparing the Minimal Depth and VIMP variable rankings.
print.gg_minimal_depth