Information Divergence: Comparing the Kullback–Leibler (KL) Divergence and the Jensen-Shannon Divergence for Comparing Distributions
Imagine standing at the edge of two vast forests. Each tree represents a data point, and the shape of the forest reflects a probability distribution. To understand how different these forests are, you could walk through both—counting, comparing, and mapping the variations. In mathematics and data science, this act of...