Uses of Class
smile.clustering.KMeans

Packages that use KMeans

Package	Description
smile.clustering	Clustering analysis.

Uses of KMeans in smile.clustering

Subclasses of KMeans in smile.clustering

Modifier and Type	Class and Description
class	DeterministicAnnealing Deterministic annealing clustering.
class	GMeans G-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters by normality test.
class	NeuralGas Neural Gas soft competitive learning algorithm.
class	XMeans X-Means clustering algorithm, an extended K-Means which tries to automatically determine the number of clusters based on BIC scores.

Methods in smile.clustering that return KMeans

Modifier and Type	Method and Description
static KMeans	KMeans.lloyd(double[][] data, int k) The implementation of Lloyd algorithm as a benchmark.
static KMeans	KMeans.lloyd(double[][] data, int k, int maxIter) The implementation of Lloyd algorithm as a benchmark.
static KMeans	KMeans.lloyd(double[][] data, int k, int maxIter, int runs) The implementation of Lloyd algorithm as a benchmark.