In data mining, machine learning and / or data science, in terms of tree analysis, there are two main approaches: decision trees and regression trees. In both cases trees are predictive methods of segmentation, known as classification trees. They are sequential partitions of the data set made to maximize the differences of the dependent variable given that a division of the cases into groups is carried out. Through different indexes and statistical procedures, the most discriminating division among the selected criteria is determined, the one that makes it possible to better differentiate the different groups from the base criterion, thus obtaining a first segmentation. From that first segmentation, new segmentations are made of each of the resulting segments and so on until the process ends with some statistical rule.
