Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 123]

▼Nkmeans	Namespace for k-means clustering
CDetails	Additional statistics from the k-means algorithm
CInitialize	Base class for initialization algorithms
CInitializeKmeanspp	k-means++ initialization of Arthur and Vassilvitskii (2007)
CInitializeKmeansppOptions	Options for k-means++ initialization
CInitializeNone	No-op "initialization" with existing cluster centers
CInitializeRandom	Initialize by sampling random observations without replacement
CInitializeRandomOptions	Options to use for InitializeRandom
CInitializeVariancePartition	Implements the variance partitioning method of Su and Dy (2007)
CInitializeVariancePartitionOptions	Options for InitializeVariancePartition
▼CMockMatrix	Compile-time interface for matrix data
CConsecutiveAccessWorkspace	Workspace for access to consecutive observations
CIndexedAccessWorkspace	Workspace for access to a indexed subset of observations
CRandomAccessWorkspace	Workspace for random access to observations
CRefine	Interface for all k-means refinement algorithms
CRefineHartiganWong	Implements the Hartigan-Wong algorithm for k-means clustering
CRefineHartiganWongOptions	Options for RefineHartiganWong
CRefineLloyd	Implements the Lloyd algorithm for k-means clustering
CRefineLloydOptions	Options for RefineLloyd construction
CRefineMiniBatch	Implements the mini-batch algorithm for k-means clustering
CRefineMiniBatchOptions	Options for RefineMiniBatch construction
CResults	Full statistics from k-means clustering
CSimpleMatrix	A simple matrix of observations