机器学习，逻辑回归，混淆矩阵，精确率示例：
from sklearn.metrics import precision_score # 1、准确数据，y_true真实结果，y_pre_A模型A预测结果，y_pre_B模型B预测结果 y_true = ['恶性','恶性','恶性','恶性','恶性','恶性','良性','良性','良性','良性'] y_pre_A = ['恶性','恶性','恶性','良性','良性','良性','良性','良性','良性','良性'] y_pre_B = ['恶性','恶性','恶性','恶性','恶性','恶性','恶性','恶性','恶性','良性'] # 2、计算精确率 print(precision_score(y_true,y_pre_A,pos_label='恶性')) print(precision_score(y_true,y_pre_B,pos_label='恶性'))