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Model Evaluation

Decision Tree

A decision tree is a diagram representing the possible outcomes of a series of interconnected choices. It allows a person or organization to evaluate different actions based on their cost, likelihood, and benefits. It can also be used to feed an informal discussion or to generate an algorithm that determines the best mathematical choice.

It usually begins with a node from which several possible outcomes may result. Each of these results leads to other nodes, which lead to other possibilities. The pattern obtained is reminiscent of the shape of a tree.

Why is the decision tree important ?

Because it can be used to build automated predictive models for applications like machine learning, data mining, or statistics. This important method involving a decision tree algorithm is called "decision tree learning". It relies on observations about an element to predict the value of that element.


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