Similarity metrics: Sometimes it doesn't matter which one you use #shorts
Channel: Lars Juhl Jensen
Date: 16/05/2022

A ~1 minute explanation of why it sometimes doesn't matter which similarity metric you use for clustering your data. In this presentation I quickly go over the math of how Pearson correlation coefficient, cosine similarity, inner product, and Euclidian distance all relate to each other in the context of centered and normalized data.