Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 12]

Ckmeans::ConsecutiveAccessExtractor< Index_, Data_ >	Extractor for accessing consecutive observations
Ckmeans::Details< Index_ >	Additional statistics from the k-means algorithm
Ckmeans::IndexedAccessExtractor< Index_, Data_ >	Extractor for accessing indexed observations
▼Ckmeans::Initialize< Index_, Data_, Cluster_, Float_, Matrix_ >	Interface for k-means initialization algorithms
Ckmeans::InitializeKmeanspp< Index_, Data_, Cluster_, Float_, Matrix_ >	k-means++ initialization of Arthur and Vassilvitskii (2007)
Ckmeans::InitializeNone< Index_, Data_, Cluster_, Float_, Matrix_ >	No-op "initialization" with existing cluster centers
Ckmeans::InitializeRandom< Index_, Data_, Cluster_, Float_, Matrix_ >	Initialize by sampling random observations without replacement
Ckmeans::InitializeVariancePartition< Index_, Data_, Cluster_, Float_, Matrix_ >	Implements the variance partitioning method of Su and Dy (2007)
Ckmeans::Initialize< Index_, Data_, Cluster_, Float_, Matrix< Index_, Data_ > >
Ckmeans::InitializeKmeansppOptions	Options for k-means++ initialization
Ckmeans::InitializeRandomOptions	Options to use for InitializeRandom
Ckmeans::InitializeVariancePartitionOptions	Options for InitializeVariancePartition
▼Ckmeans::Matrix< Index_, Data_ >	Interface for matrix data
Ckmeans::SimpleMatrix< Index_, Data_ >	A simple matrix of observations
Ckmeans::RandomAccessExtractor< Index_, Data_ >	Extractor for accessing random observations
▼Ckmeans::Refine< Index_, Data_, Cluster_, Float_, Matrix_ >	Interface for k-means refinement algorithms
Ckmeans::RefineHartiganWong< Index_, Data_, Cluster_, Float_, Matrix_ >	Implements the Hartigan-Wong algorithm for k-means clustering
Ckmeans::RefineLloyd< Index_, Data_, Cluster_, Float_, Matrix_ >	Implements the Lloyd algorithm for k-means clustering
Ckmeans::RefineMiniBatch< Index_, Data_, Cluster_, Float_, Matrix_ >	Implements the mini-batch algorithm for k-means clustering
Ckmeans::Refine< Index_, Data_, Cluster_, Float_, Matrix< Index_, Data_ > >
Ckmeans::RefineHartiganWongOptions	Options for RefineHartiganWong
Ckmeans::RefineLloydOptions	Options for RefineLloyd construction
Ckmeans::RefineMiniBatchOptions	Options for RefineMiniBatch construction
Ckmeans::Results< Index_, Cluster_, Float_ >	Full statistics from k-means clustering