Plots.roc_curve(target_num: int = 0) → Tuple[numpy.ndarray, numpy.ndarray][source]

Returns the data for the ROC curve, as displayed in the getML monitor.

This requires that you call score() first. The data used for the curve will always be the data from the last time you called score().

target_num (int):

Indicates for which target you want to plot the lift curve. (Pipelines can have more than one target.)

(numpy.ndarray, numpy.ndarray):
  • The first array is the false positive rate, usually displayed on the x-axis.

  • The second array is the true positive rate, usually displayed on the y-axis.