Cosine Similarity is a measure that ignores the magnitude of the distance between two non-zero vectors thus acting as strictly a judgement of orientation. Two vectors with the same orientation have a cosine similarity of 1, whereas two vectors oriented at 90° relative to each other have a similarity of 0, and two vectors diametrically opposed have a similarity of -1. To be used as a distance function, we subtract the Cosine Similarity from 1 in order to satisfy the positive semi-definite condition, therefore the Cosine distance is a number between 0 and 2.
Note: This distance kernel is optimized for sparse (mainly zeros) coordinate vectors.
Data Type Compatibility: Continuous
This kernel does not have any parameters.
use Rubix\ML\Kernels\Distance\Cosine; $kernel = new Cosine();