from sklearn.metrics import confusion_matrix
import pandas as pd

# 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、混淆矩阵 模型A
A = confusion_matrix(y_true,y_pre_A,labels=['恶性','良性'])
print(pd.DataFrame(A,columns=['恶性','良性'],index=['恶性','良性']))

# 3、混淆矩阵 模型B
B = confusion_matrix(y_true,y_pre_B,labels=['恶性','良性'])
print(pd.DataFrame(B,columns=['恶性','良性'],index=['恶性','良性']))