ML Interview Question: Explain the concept of entropy in decision trees?

KAMAL

Decision tree is one algorithm used in supervised learning. Entropy plays an important role in this. You should explain entropy first and then what is it's role in decision trees?

Niranjan sahoo

In the context of Decision Trees, entropy is a measure of disorder or impurity in a node. Thus, a node with more variable composition, such as 2Pass and 2 Fail would be considered to have higher Entropy than a node which has only pass or only fail.