Decision Tree Learning

Decision Tree Learning is one of the most successful techniques for supervised classification learning. It is one of the most widely used and practical methods for inductive inference. Decision tree learning is a methods for approximating discrete – valued target function, in which the learned function is represented by a decision tree. It is a method commonly used in data mining. The goal is to create a model that predicts the value of a target variable based on several input variables.