cluster

Documentation

Index

• type KMeansClassifier
  • func NewKMeansClassifier(k int, maxIterations int) *KMeansClassifier
  • func (kmc *KMeansClassifier) ClusterCentroids() []ml.Datum
  • func (kmc *KMeansClassifier) Fit(input []ml.Datum) ([]int, int, error)

Types

type KMeansClassifier

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

KMeansClassifier finds the k cluster centroids which minimize the associative

distances with the training input.

func NewKMeansClassifier

func NewKMeansClassifier(k int, maxIterations int) *KMeansClassifier

NewKMeansClassifier constructs a KMeansClassifier

func (*KMeansClassifier) ClusterCentroids

func (kmc *KMeansClassifier) ClusterCentroids() []ml.Datum

ClusterCentroids returns the centroids

func (*KMeansClassifier) Fit

func (kmc *KMeansClassifier) Fit(input []ml.Datum) ([]int, int, error)

Fit finds the KMeans centroids given the input and saves the result.

the number of values that associate with each centroid and the number of iterations
is returned