def plot_confusion_matrix(cm, class_names):
Returns a matplotlib figure containing the plotted confusion matrix.
cm (array, shape = [n, n]): a confusion matrix of integer classes
class_names (array, shape = [n]): String names of the integer classes
figure = plt.figure(figsize=(8, 8))
plt.imshow(cm, interpolation='nearest', cmap=plt.cm.Blues)
plt.title("Confusion matrix")
tick_marks = np.arange(len(class_names))
plt.xticks(tick_marks, class_names, rotation=45)
plt.yticks(tick_marks, class_names)
# Normalize the confusion matrix.
cm = np.around(cm.astype('float') / cm.sum(axis=1)[:, np.newaxis], decimals=2)
# Use white text if squares are dark; otherwise black.
threshold = cm.max() / 2.
for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):
color = "white" if cm[i, j] > threshold else "black"
plt.text(j, i, cm[i, j], horizontalalignment="center", color=color)
plt.xlabel('Predicted label')