ndarray-simd/com.martmists.ndarray.simd.math/clusterKMeans

clusterKMeans

fun clusterKMeans(k: Int, points: List<F64FlatArray>): Map<F64FlatArray, Cluster>
fun clusterKMeans(k: Int, points: Array<F64FlatArray>): Map<F64FlatArray, Cluster>
@JvmName(name = "clusterKMeansND")
fun clusterKMeans(k: Int, points: List<F64Array>): Map<F64FlatArray, Cluster>
fun clusterKMeans(k: Int, points: Array<F64Array>): Map<F64FlatArray, Cluster>

Cluster the points into k clusters using K-means clustering.

Return

A map of size k from centroid to cluster

Since

1.4.1

Parameters

k

The number of clusters

points

The points to cluster