similarity measure

Terms from Artificial Intelligence: humans at the heart of algorithms

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 {\em similarity} measure this would usually be inverted in some way (e.g. 1/distance).

Used in Chap. 7: pages 91, 92; Chap. 8: page 108; Chap. 9: page 118; Chap. 10: pages 134, 141; Chap. 12: page 185; Chap. 16: pages 240, 242, 248; Chap. 18: page 286; Chap. 21: page 340

Also known as similarity, similarity metrics