import numpyfrom sklearn import metrics# 生成模拟数据（90% 概率为 1 的二元分类数据）actual = numpy.random.binomial(1, 0.9, size=1000)predicted = numpy.random.binomial(1, 0.9, size=1000)# 计算敏感度/召回率（正类别的识别率）：Sensitivity_recall = metrics.recall_score(actual, predicted)print(Sensitivity_recall)