We propose the use of projection correlation to characterize dependence between two random vectors. Projection correlation has several appealing properties. It equals zero if and only if the two ...

In model-based clustering, the relevant distance measurement is called the Mahalanobis distance, which is the Euclidean distance scaled by the covariance between vectors 16.

Similarity search is based on finding the distance between two vectors and retrieving the closest. The vectors are numerical representations of words or phrases.

Another metric, the cosine similarity, is often used for text processing, where the direction of the embedding vectors is important but the distance between them is not.