Trait reductive::kmeans::KMeans

pub trait KMeans<A> {
    fn k_means(
        &self, 
        instance_axis: Axis, 
        k: usize, 
        initial_centroids: impl InitialCentroids<A>, 
        stop_condition: impl StopCondition<A>
    ) -> (Array2<A>, A);
}

Trait for types that implement k-means clustering.

Required methods

fn k_means(
    &self,
    instance_axis: Axis,
    k: usize,
    initial_centroids: impl InitialCentroids<A>,
    stop_condition: impl StopCondition<A>
) -> (Array2<A>, A)

Perform k-means clustering.

Performs k-means clustering on the matrix of instances along the given instance_axis.

Returns the k x d matrix of cluster centroids and the mean mean-squared error.

Implementations on Foreign Types

impl<'a, S, A> KMeans<A> for ArrayBase<S, Ix2> where
    S: Data<Elem = A>,
    A: NdFloat + Sum,
    usize: AsPrimitive<A>, 

fn k_means(
    &self,
    instance_axis: Axis,
    k: usize,
    initial_centroids: impl InitialCentroids<A>,
    stop_condition: impl StopCondition<A>
) -> (Array2<A>, A)

Implementors