Below are some assumptions that we made while using decision tree: At the beginning, we consider the whole training set as the root. Feature values are preferred to be categorical. If the values are continuous then they are discretized prior to building the model. On the basis of attribute values records are distributed recursively. We use statistical methods for ordering attributes as root or the internal node.