kmeans

Documentation

Overview

Package kmeans clusters incoming points into clusters with params (eps, minPoints) K-Means performs the division of objects into clusters that share similarities and are dissimilar to the objects belonging to another cluster. The term ‘K’ is a number. You need to tell the system how many clusters you need to create. For example, K = 2 refers to two clusters.

Index

• type Kmeans
  • func New() Kmeans
  • func NewWithOptions(deltaThreshold float64) (Kmeans, error)
  • func (m Kmeans) Partition(dataset clusters.PointList, k int) (clusters.Clusters, error)

Types

type Kmeans

type Kmeans struct {
	// contains filtered or unexported fields
}

Kmeans configuration/option struct

func New

func New() Kmeans

New returns a Kmeans configuration struct with default settings

func NewWithOptions

func NewWithOptions(deltaThreshold float64) (Kmeans, error)

NewWithOptions returns a Kmeans configuration struct with custom settings

func (Kmeans) Partition

func (m Kmeans) Partition(dataset clusters.PointList, k int) (clusters.Clusters, error)

Partition executes the k-means algorithm on the given dataset and partitions it into k clusters