Receiver Operator Characteristic calculator

Usage

# S3 method for class 'rfsrc'
calc_roc(object, dta, which_outcome = "all", oob = TRUE, ...)

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

Value

A gg_roc object

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.

Examples

## Taken from the gg_roc example
rfsrc_iris <- rfsrc(Species ~ ., data = 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$yvar,
  which_outcome = 1
)
#> Warning: number of rows of result is not a multiple of vector length (arg 2)
gg_dta <- calc_roc(rf_iris, rf_iris$yvar,
  which_outcome = 2
)