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A metric function (or distance) is a generalization of geometric distance (i.e. Euclidean Distance)

Direct similarity measures are not always reliable for high-dimensional clustering (see Guha1999)

Similarity is the opposite of distance

- usually can be turned to distance
- Cosine Similarity and Dot Product
- Jaccard Coefficient

Non-metric

- Strehl, Alexander, Joydeep Ghosh, and Raymond Mooney. "Impact of similarity measures on web-page clustering." 2000. [1]
- Guha, Sudipto, Rajeev Rastogi, and Kyuseok Shim. "ROCK: A robust clustering algorithm for categorical attributes." 1999. [2]