Concept Drift in Machine Learning 101
As machine learning models become more and more popular solutions for automation and prediction tasks, many tech companies and data...
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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 
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
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