sklearn plot confusion matrix with labels

Question

I want to plot a confusion matrix to visualize the classifer\'s performance, but it shows only the numbers of the labels, not the labels themselves:

from skl         


        

Answer 1

To add to @akilat90's update about sklearn.metrics.plot_confusion_matrix:

You can use the ConfusionMatrixDisplay class within sklearn.metrics directly and bypass the need to pass a classifier to plot_confusion_matrix. It also has the display_labels argument, which allows you to specify the labels displayed in the plot as desired.

The constructor for ConfusionMatrixDisplay doesn't provide a way to do much additional customization of the plot, but you can access the matplotlib axes obect via the ax_ attribute after calling its plot() method. I've added a second example showing this.

I found it annoying to have to rerun a classifier over a large amount of data just to produce the plot with plot_confusion_matrix. I am producing other plots off the predicted data, so I don't want to waste my time re-predicting every time. This was an easy solution to that problem as well.

Example:

from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay

cm = confusion_matrix(y_true, y_preds, normalize='all')
cmd = ConfusionMatrixDisplay(cm, display_labels=['business','health'])
cmd.plot()

Example using ax_:

cm = confusion_matrix(y_true, y_preds, normalize='all')
cmd = ConfusionMatrixDisplay(cm, display_labels=['business','health'])
cmd.plot()
cmd.ax_.set(xlabel='Predicted', ylabel='True')