Feature Request
The dictionary returned by plot.rocCurve has Figure, Axes, POD, POFD, and Thresholds.
It'd be extremely useful to add the area under the curve (AUC) as a measure of model performance.
Currently the implementation uses Contingency2x2.fromBoolean() and loops over thresholds creating a new Contingency2x2 object each time. It might be good to consider directly supporting probabilistic predictions, possibly in a similar manner to fromBoolean - this could them allow updating of the contingency table by updating the threshold as the probabilities would be stored with the object (and would allow bootstrapping CIs, same as fromBoolean).
AUC could then be calculated without the ROC plotting.
Feature Request
The dictionary returned by
plot.rocCurvehasFigure,Axes,POD,POFD, andThresholds.It'd be extremely useful to add the area under the curve (AUC) as a measure of model performance.
Currently the implementation uses
Contingency2x2.fromBoolean()and loops over thresholds creating a newContingency2x2object each time. It might be good to consider directly supporting probabilistic predictions, possibly in a similar manner tofromBoolean- this could them allow updating of the contingency table by updating the threshold as the probabilities would be stored with the object (and would allow bootstrapping CIs, same asfromBoolean).AUC could then be calculated without the ROC plotting.