# Similarity Measures ## Cosine similarity Cosine similarity is the dot product of two vectors, normalized by the product of the length of the vectors. It calculates the angle between two vectors and is therefore length-independent. Its values ranges from 0 to 1. $ \cos (\theta)=\frac{\sum v 1_{k} * v 2_{k}}{\sqrt{\sum v 1_{k}^{2}} * \sqrt{\sum v 2_{k}^{2}}} $ ## Jacard Similarity It is defined as the ratio of the size of the intersection of sets A and B to the size of their union, given as $ J(A, B)=\frac{|A \cap B|}{|A \cup B|} $ ## KL Divergence Distance - [[Jensen–Shannon Divergence]] ## Optimal Transport Based - [[Wasserstein Distance]] --- ## References