CoOL_4_AUC: Plot the ROC AUC

In ekstroem/CoOL: Causes of Outcome Learning

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

#See the example under CoOL_0_working_example

ekstroem/CoOL documentation built on June 1, 2022, 12:33 p.m.