mlpack_kmeans3

Classes

class AllowEmptyClusters
Policy which allows K-Means to create empty clusters without any error being reported. class KMeans
This class implements K-Means clustering. class MaxVarianceNewCluster
When an empty cluster is detected, this class takes the point furthest from the centroid of the cluster with maximum variance as a new cluster. class RandomPartition
A very simple partitioner which partitions the data randomly into the number of desired clusters. class RefinedStart
A refined approach for choosing initial points for k-means clustering.