distributions.py 文件源码

def sklearn_purity_completeness(score_export):
    golds, probs = zip(*score_export.roc())
    golds = np.array(golds)
    probs = np.array(probs)

    purity, completeness, _ = precision_recall_curve(golds, probs)

    plt.clf()
    plt.plot(completeness, purity, lw=2, color='navy',
             label='Precision-Recall curve')
    plt.xlabel('Recall')
    plt.ylabel('Precision')
    plt.ylim([0.0, 1.05])
    plt.xlim([0.0, 1.0])
    # plt.title('Precision-Recall example: AUC={0:0.2f}'.format(average_precision[0]))
    plt.legend(loc="lower left")
    # plt.show()