ssl_plots.py

# Plot f1 scores and number of pseudo-labels added for all iterations

fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(6,8))
ax1.plot(range(iterations), test_f1s)
ax1.set_ylabel('f1 Score')
ax2.bar(x=range(iterations), height=pseudo_labels)
ax2.set_ylabel('Pseudo-Labels Created')
ax2.set_xlabel('# Iterations');

# View confusion matrix after self-training

plot_confusion_matrix(clf, X_test, y_test, cmap='Blues', normalize='true',
                     display_labels=['No Comp.', 'Complication']);