有没有办法用已知的真阳性、真阴性、假阳性和假阴性来绘制混淆矩阵？

Question

Today I have finished processing some data and came to conclusion that I have the following final tables containing:

	Counts.
True Positive	23070
True Negative	4503
False Positive	28
False Negative	34

I am trying to construct a confusion matrix here, scikit-learn.confusion_matrix style, but I cant figure out how. Can I use Matplotlib for this instead? Do you guys ever come to his type of quest? I believe we can draw it somehow. Thank you!

Answer 1

With scikit-learn.confusion_matrix You can get the confusion matrix by
cm = confusion_matrix(y_true, y_pred)

And the confusion matrix is already in the form
TP|FN
FP|TN

You can use seaborn's heatmap to plot the data:

import seaborn as sns
sns.heatmap(cm, annot=True, cmap='Blues')

If you already have the data then try storing it in a list of list then plot the data using seaborn:

cm_data = [[23070, 34], [4503, 28]]
sns.heatmap(cm_data, annot=True, cmap='Blues', fmt='d')