docs: def plot_confusion_matrix(self, normalised=True):
          """
          Plots the confusion matrix.
          """
          conf_matrix = self.confusion_matrix()
  
          if normalised:
              sns.heatmap(conf_matrix,
                          annot=True, annot_kws={"size": 12}, fmt='2.1f', cmap='YlGnBu', vmin=0.0,
                          vmax=100.0,
                          xticklabels=list(self.class_dictionary.keys()),
                          yticklabels=self.truth_classes)
          else:
              sns.heatmap(self.pixel_classification_counts,
                          annot=True, annot_kws={"size": 12}, fmt='2.1f', cmap='YlGnBu', vmin=0.0,
                          vmax=np.max(self.pixel_classification_counts),
                          xticklabels=list(self.class_dictionary.keys()),
                          yticklabels=self.truth_classes)