Decision Tree — the smartest tree we know

AI enthusiasts, we have great news for you! Our article series based on Synaptech’s glossary continues! Today’s topic is Decision Tree, a tree unlike any other, while our latest was about Convolutional Neural Networks.

credits analyticsvidhya.com

What is a Decision Tree?

A decision tree is a predictive algorithmic model that goes from the observations of an object (branches) to the conclusions about the object’s value (leaves). Its purpose is to predict modelling approaches in statistics, data mining and machine learning.

Regarding the types the decision tree is used, the way it is implemented can vary. For instance, for a decision analysis, the decision tree can be chose to represent in a visual and explicit manner the decisions, while in data mining, a decision tree describes data. In the resulting classification, the tree can be justified as an input for decision making.

Types of Decision Trees

Just like any other ML algorithm, the decision tree has plenty of types. There are two main types managed in data mining:

• Classification tree — its goal is to create rules that can be explained and translated into software language. It records, labels and assigns variables to classes. A classification tree is built through a process also known as binary recursive partitioning. The process implies splitting data into partitions and then splitting them up further on each of the branches.
• Regression Trees — this type deals with a continuous goal variable. The methods perform induction by means of an efficient recursive partitioning algorithm. Briefly, regression trees provide good predictive accuracy on many domains. However, the simple models used in their leaves have some limitations regarding the kind of functions they are able to perform.
• Decision stream — it’s a diagram which illustrates the information or process flow in a system or subsystem.

If you want to add some details or share your opinion this algorithm, feel free to share them with us in a comment. Meanwhile, stay tuned for our next article about AI terms, Generative adversarial networks.