ggRandomForests (version 2.2.0)

calc_roc.rfsrc: Receiver Operator Characteristic calculator

Description

Receiver Operator Characteristic calculator

Usage

# S3 method for rfsrc
calc_roc(object, dta, which.outcome = "all", oob = TRUE, ...)

Value

A gg_roc object

Arguments

object

rfsrc or predict.rfsrc object containing predicted response

dta

True response variable

which.outcome

If defined, only show ROC for this response.

oob

Use OOB estimates, the normal validation method (TRUE)

...

extra arguments passed to helper functions

Details

For a randomForestSRC prediction and the actual response value, calculate the specificity (1-False Positive Rate) and sensitivity (True Positive Rate) of a predictor.

This is a helper function for the gg_roc functions, and not intended for use by the end user.

See Also

calc_auc gg_roc

plot.gg_roc

Examples

## Taken from the gg_roc example
# rfsrc_iris <- rfsrc(Species ~ ., data = iris)
data(rfsrc_iris)

gg_dta <- calc_roc(rfsrc_iris, rfsrc_iris$yvar,
     which.outcome=1, oob=TRUE)
gg_dta <- calc_roc(rfsrc_iris, rfsrc_iris$yvar,
     which.outcome=1, oob=FALSE)

rf_iris <- randomForest(Species ~ ., data = iris)
gg_dta <- calc_roc(rf_iris, rf_iris$yvar,
     which.outcome=1)
gg_dta <- calc_roc(rf_iris, rf_iris$yvar,
     which.outcome=2)