How to find entropy in Machine Learning?

Question

Can anyone tell me how to find entropy in Machine Learning?

Answer 1

Entropy is usually calculated when you build decision trees. It is calculated using the following formula:

Entropy = -SUM(Pi * log2(Pi))

Where Pi (read ‘P of i’) is the proportion of a node belonging to a particular class. Its value ranges from 0 to 1 with ‘1’ being maximum entropy and ‘0’ being minimum entropy.

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