Precision / Recall curve

precision_recall_plot.py

from sklearn.metrics import precision_score, recall_score, precision_recall_curve
import matplotlib.pyplot as plt


def plt_prc(recall, precision, label=None):
    plt.step(recall, precision, label=label)
    plt.xlabel('Recall')
    plt.ylabel('Precision')
    plt.ylim([0.0, 1.05])
    plt.xlim([0.0, 1.0])

precision, recall, thresholds = precision_recall_curve(data['label'], data['probability']
_ = plt_prc(recall, precision, label=f'PRC {<description of plot>}')