Enum DistanceCalculationMetric 

pub enum DistanceCalculationMetric {
    Euclidean,
    Manhattan,
    Minkowski(f64),
}

Represents different distance calculation methods used in various machine learning algorithms.

This enum defines common distance metrics that can be used in clustering algorithms, nearest neighbor searches, and other applications where distance between points is relevant.

Variants

• Euclidean - Euclidean distance (L2 norm), calculated as the square root of the sum of squared differences between corresponding coordinates.
• Manhattan - Manhattan distance (L1 norm), calculated as the sum of absolute differences between corresponding coordinates.
• Minkowski - A generalized metric that includes both Euclidean and Manhattan distances as special cases. Requires an additional parameter p (f64).

Variants

Euclidean

Manhattan

Minkowski(f64)

Trait Implementations

impl Clone for DistanceCalculationMetric

fn clone(&self) -> DistanceCalculationMetric

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for DistanceCalculationMetric

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for DistanceCalculationMetric

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for DistanceCalculationMetric

fn eq(&self, other: &DistanceCalculationMetric) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for DistanceCalculationMetric

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for DistanceCalculationMetric

impl StructuralPartialEq for DistanceCalculationMetric