Struct CompensatedCosineNormalized 

pub struct CompensatedCosineNormalized { /* private fields */ }

Compensated CosineNormalized distance function.

Implementations

impl CompensatedCosineNormalized

pub fn new(scale_squared: f32) -> Self

Trait Implementations

impl AsFunctor<CompensatedCosineNormalized> for ScalarQuantizer

fn as_functor(&self) -> CompensatedCosineNormalized

impl Clone for CompensatedCosineNormalized

fn clone(&self) -> CompensatedCosineNormalized

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CompensatedCosineNormalized

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<const NBITS: usize> DistanceFunction<VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, Result<MathematicalValue<f32>, UnequalLengths>> for CompensatedCosineNormalized

where Unsigned: Representation<NBITS>, SquaredL2: for<'a, 'b> PureDistanceFunction<BitSlice<'a, NBITS, Unsigned>, BitSlice<'b, NBITS, Unsigned>, MathematicalResult<u32>>,

CosineNormalized

This implementation calculates the <x, y> = 1 - L2 / 2 value, which will be further used to compute the CosineNormalised distance function

Notes

s = 1 - cosine(X, Y) = 1- <X, Y> / (||X|| * ||Y||)

We can make simply assumption that ||X|| = 1 and ||Y|| = 1. Then s = 1 - <X, Y>

The squared L2 distance can be computed as follows: p = ||x||^2 + ||y||^2 - 2<x, y> When vectors are normalized, this becomes p = 2 - 2<x, y> = 2 * (1 - <x, y>)

In other words, the similarity score for the squared L2 distance in an ideal world is 2 times that for cosine similarity. Therefore, squared L2 may serves as a stand-in for cosine normalized as ordering is preserved.

fn evaluate_similarity( &self, x: CompensatedVectorRef<'_, NBITS>, y: CompensatedVectorRef<'_, NBITS>, ) -> MathematicalResult<f32>

Perform a distance computation between the left-hand and right-hand arguments.

impl<const NBITS: usize> DistanceFunction<VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, VectorBase<NBITS, Unsigned, SlicePtr<'_, u8>, Ref<'_, Compensation>>, Result<f32, UnequalLengths>> for CompensatedCosineNormalized

where Unsigned: Representation<NBITS>, Self: for<'a, 'b> DistanceFunction<CompensatedVectorRef<'a, NBITS>, CompensatedVectorRef<'b, NBITS>, MathematicalResult<f32>>,

fn evaluate_similarity( &self, x: CompensatedVectorRef<'_, NBITS>, y: CompensatedVectorRef<'_, NBITS>, ) -> Result<f32>

Perform a distance computation between the left-hand and right-hand arguments.

impl Copy for CompensatedCosineNormalized