Decision Trees are the most common machine learning algorithm used for the classification and regression of data. This supervised mechanism splices data per subset into various groups until it reaches the leaf node, where it cannot be divided further. Since this data will be split into categories based on the provided attributes, it will be evenly split. It conveys that both data that went through normalisation and data that didn’t would have the same number of splits. Therefore, normalisation is not a prerequisite for decision-based tree models.