NAME¶
mlpack::kmeans -
K-Means clustering.
SYNOPSIS¶
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.
Detailed Description¶
K-Means clustering.
Author¶
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