class |
AlternatingKMedoids<O> |
A k-medoids clustering algorithm, implemented as EM-style batch algorithm;
known in literature as the "alternate" method.
|
class |
CLARA<V> |
Clustering Large Applications (CLARA) is a clustering method for large data
sets based on PAM, partitioning around medoids ( PAM ) based on
sampling.
|
class |
CLARANS<O> |
CLARANS: a method for clustering objects for spatial data mining
is inspired by PAM (partitioning around medoids, PAM )
and CLARA and also based on sampling.
|
class |
EagerPAM<O> |
Variation of PAM that eagerly performs all swaps that yield an improvement
during an iteration.
|
class |
FastCLARA<V> |
Clustering Large Applications (CLARA) with the FastPAM
improvements, to increase scalability in the number of clusters.
|
class |
FastCLARANS<V> |
A faster variation of CLARANS, that can explore O(k) as many swaps at a
similar cost by considering all medoids for each candidate non-medoid.
|
class |
FasterCLARA<O> |
Clustering Large Applications (CLARA) with the FastPAM
improvements, to increase scalability in the number of clusters.
|
class |
FasterPAM<O> |
Variation of FastPAM that eagerly performs any swap that yields an
improvement during an iteration.
|
class |
FastPAM<O> |
FastPAM: An improved version of PAM, that is usually O(k) times faster.
|
class |
FastPAM1<O> |
FastPAM1: A version of PAM that is O(k) times faster, i.e., now in O((n-k)²).
|
class |
PAM<O> |
The original Partitioning Around Medoids (PAM) algorithm or k-medoids
clustering, as proposed by Kaufman and Rousseeuw; a largely equivalent method
was also proposed by Whitaker in the operations research domain, and is well
known by the name "fast interchange" there.
|
class |
ReynoldsPAM<O> |
The Partitioning Around Medoids (PAM) algorithm with some additional
optimizations proposed by Reynolds et al.
|
class |
SingleAssignmentKMedoids<O> |
K-medoids clustering by using the initialization only, then assigning each
object to the nearest neighbor.
|