A decision tree can be used for classification or regression. It operates by dividing the data into smaller and smaller subgroups in a tree-like arrangement. When estimating the output value of a set of characteristics, it will do so based on the subset into which the set of features falls.
The purpose of employing a Choice Tree is to build a training model that can predict the class or value of a target variable by learning basic decision rules from prior data (training data).
Decision trees assist you in weighing your options. Decision trees are fantastic tools for assisting you in deciding between multiple options. They give a highly effective structure for laying out options and investigating the potential outcomes of those options.