Calculates Cosine similarity between two vectors.

https://en.wikipedia.org/wiki/Cosine_similarity#Definition

Example:

Similarity.cosine([1, 2, 3], [1, 2, 8])

Multiplies cosine similarity with the square root of compared vectors length.

srol here means square root of length

This gives better comparable numbers where the number of attributes compared might differ. You can try to use this instead of cosine/2 if the number of shared attributes differ.

Example:

Similarity.cosine_srol([1, 2, 3], [1, 2, 8])

Calculates Euclidean dot product of two vectors.

https://en.wikipedia.org/wiki/Euclidean_vector#Dot_product

Example:

iex> Similarity.dot_product([1, 2], [3, 4])
11

Calculates Euclidean magnitude of one vector.

https://en.wikipedia.org/wiki/Magnitude_(mathematics)#Euclidean_vector_space

Example:

iex> Similarity.magnitude([2])
2.0

For docs see Similarity.Simhash

For docs see Similarity.SorensenDice