Confusion Matrix Cheatsheet


Let’s say that you have two arrays which are telling you the true labels y_true and the predicted labels y_pred. Additionally, you have a variable classes, which contains all of the classes. Then let’s first import the necessary libraries: pandas, seaborn and sklearn

from sklearn.metrics import confusion_matrix
import pandas as pd
import seaborn as sns

Then create the confusion matrix, put it into a Pandas DataFrame where the index and columns are the classes

cm = confusion_matrix(y_true, y_pred)
df_cm = pd.DataFrame(cm, index=classes, columns=classes)

Finally, plot it:

fig, ax = plt.subplots(dpi=200)
sns.heatmap(df_cm, annot=True, fmt="d", ax=ax)
ax.set_xlabel("Estimated Label")
ax.set_ylabel("True Label")