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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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)