CoOL (version 1.1.2)

CoOL_4_AUC: Plot the ROC AUC

Description

Plot the ROC AUC

Usage

CoOL_4_AUC(
  outcome_data,
  exposure_data,
  model,
  title = "Receiver operating\ncharacteristic curve",
  restore_par_options = TRUE
)

Arguments

outcome_data

The outcome data.

exposure_data

The exposure data.

model

The fitted the non-negative neural network.

title

Title on the plot.

restore_par_options

Restore par options.

Value

A plot of the ROC and the ROC AUC value.

References

Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. 2022. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. International Journal of Epidemiology <https://doi.org/10.1093/ije/dyac078>

Examples

# NOT RUN {
#See the example under CoOL_0_working_example
# }