python - sklearn 绘制带有标签的混淆矩阵

Question

我想绘制一个混淆矩阵来可视化分类器的性能，但它只显示标签的数量，而不是标签本身:

from sklearn.metrics import confusion_matrix
import pylab as pl
y_test=['business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business', 'business']

pred=array(['health', 'business', 'business', 'business', 'business',
       'business', 'health', 'health', 'business', 'business', 'business',
       'business', 'business', 'business', 'business', 'business',
       'health', 'health', 'business', 'health'], 
      dtype='|S8')

cm = confusion_matrix(y_test, pred)
pl.matshow(cm)
pl.title('Confusion matrix of the classifier')
pl.colorbar()
pl.show()

如何将标签(健康、业务等)添加到混淆矩阵中？

Answer 1

更新:

在 scikit-learn 0.22 中，有一个新功能可以直接绘制混淆矩阵(但是，该功能在 1.0 中已弃用，将在 1.2 中删除)。

查看文档:sklearn.metrics.plot_confusion_matrix

---

旧答案:

我认为值得一提的是 seaborn.heatmap 的使用在这里。

import seaborn as sns
import matplotlib.pyplot as plt     

ax= plt.subplot()
sns.heatmap(cm, annot=True, fmt='g', ax=ax);  #annot=True to annotate cells, ftm='g' to disable scientific notation

# labels, title and ticks
ax.set_xlabel('Predicted labels');ax.set_ylabel('True labels'); 
ax.set_title('Confusion Matrix'); 
ax.xaxis.set_ticklabels(['business', 'health']); ax.yaxis.set_ticklabels(['health', 'business']);