9 Distance Measures in Data Science

The advantages and pitfalls of common distance measures

Distance Measures. Image by the author.

Many algorithms, whether supervised or unsupervised, make use of distance measures. These measures, such as euclidean distance or cosine similarity, can often be found in algorithms such as k-NN, UMAP, HDBSCAN, etc.