Decision Tree Classifier Explained

With video explanation | Data Series | Episode 11.1

In this episode, we focus on explaining decision tree classifiers and how they are built using Entropy and Information Gain.

What is a Decision Tree?

A Decision Tree is an algorithm that splits our data according to decisions in order to classify or predict data.

Decision Trees can be used for both regression and classification problems and are an example of a supervised machine learning algorithm.

Example of a Decision Tree:

Decision Trees have certain properties shown below:

Building a Decision Tree

To see how to build a decision Tree, let us look at two possible splits we can make on our data: