🎉 AI Engineers: Join our free webinar on how to improve your RAG performance. Secure your spot >

To Glossary Lobby

What is Jensen-Shannon Divergence in Machine Learning

Jensen-Shannon Divergence is a type of statistical method for concept drift detection, using the KL divergence.

Where M = \frac{Q+P}{2}  the mean between P and Q

The main differences between JS divergence and KL divergence are that JS is symmetric and it always has a finite value

Concept drift detection method
Concept drift detection method

Learn more about these concepts in our articles:

Green Design
Green Background

Control All your GenAI Apps in minutes