# precision_recall_curve¶

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

Returns the data for the precision-recall 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().

Args:
target_num (int):

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

Return:
(numpy.ndarray, numpy.ndarray):
• The first array is the recall (a.k.a. true postive rate), usually displayed on the x-axis.

• The second array is the precision, usually displayed on the y-axis.