Struct smartcore::cluster::kmeans::KMeansParameters

pub struct KMeansParameters {
    pub k: usize,
    pub max_iter: usize,
    pub seed: Option<u64>,
}

K-Means clustering algorithm parameters

Fields

k: usize

Number of clusters.

max_iter: usize

Maximum number of iterations of the k-means algorithm for a single run.

seed: Option<u64>

Determines random number generation for centroid initialization. Use an int to make the randomness deterministic

Implementations

impl KMeansParameters

pub fn with_k(self, k: usize) -> Self

Number of clusters.

pub fn with_max_iter(self, max_iter: usize) -> Self

Maximum number of iterations of the k-means algorithm for a single run.

Trait Implementations

impl Clone for KMeansParameters

fn clone(&self) -> KMeansParameters

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for KMeansParameters

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

Formats the value using the given formatter.

impl Default for KMeansParameters

fn default() -> Self

Returns the “default value” for a type.

impl<TX: Number, TY: Number, X: Array2<TX>, Y: Array1<TY>> UnsupervisedEstimator<X, KMeansParameters> for KMeans<TX, TY, X, Y>

fn fit(x: &X, parameters: KMeansParameters) -> Result<Self, Failed>

Fit a model to a training dataset, estimate model’s parameters.