Decision tree (DT) analysis is a general and predictive modeling tool for machine learning. It is one of the simplest and most useful structures for machine learning. As the name indicates, DTs are trees of decisions. By using an algorithm approach for splitting data sets according to different conditions, decision trees are constructed. A decision tree is one of the commonly used and functional techniques for supervised learning.
But before moving on to designing decision trees with pruning, let’s understand its true concept.