Enum DistanceMetric 

pub enum DistanceMetric {
    Euclidean,
    Manhattan,
    Cosine,
}

Enumeration of distance metrics for mathematical computations.

This enum defines common distance metrics used in machine learning, clustering, and similarity calculations. Each variant represents a different approach to measuring the distance between points or vectors.

Variants

Euclidean

Euclidean distance (L2 norm) - straight-line distance between points

Manhattan

Manhattan distance (L1 norm) - sum of absolute differences along each dimension

Cosine

Cosine distance - measures the cosine of the angle between vectors

Trait Implementations

impl Clone for DistanceMetric

fn clone(&self) -> DistanceMetric

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DistanceMetric

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

Formats the value using the given formatter.

impl Copy for DistanceMetric