Given two data items, we often need to calculate some measure or metric of how similar they are. For example, this may be used by a clustering algorithm. For discrete valued features this might simply be a count of how many features are identical. For continuous valued feature some distance measure may be used, such as Euclidean distance or Manhatten block distance, but to be a similarity measure this would usually be inverted in some way (e.g. 1/distance) so that higher values are more similar.
Also known as: similarity, similarity metrics
Used in glossary entries: clustering, Euclidean distance