Modifier and Type | Interface and Description |
---|---|
interface |
DistanceClusterer<CLUSTERS extends IndexClusters>
A
DistanceClusterer clusters data that can be represented as a distance
matrix. |
interface |
SimilarityClusterer<CLUSTERS extends IndexClusters>
A
SimilarityClusterer clusters data that can be represented as a similarity
matrix. |
Modifier and Type | Class and Description |
---|---|
class |
ContectedComponentSimilarityClusterer
Cluster based on connected components.
|
class |
DistanceDBSCAN
DBSCAN using a SparseMatrix of distances |
class |
SimilarityDBSCAN
DBSCAN using a SparseMatrix of similarities |
class |
SparseMatrixDBSCAN
Implementation of DBSCAN (http://en.wikipedia.org/wiki/DBSCAN) using
a
|
Modifier and Type | Class and Description |
---|---|
class |
IncrementalLifetimeSparseClusterer
An
IncrementalSparseClusterer which also has a notion of a lifetime. |
class |
IncrementalSparseClusterer
An incremental clusterer which holds old
SparseMatrix instances internally,
only forgetting rows once they have been clustered and are relatively stable. |
Constructor and Description |
---|
IncrementalLifetimeSparseClusterer(SparseMatrixClusterer<? extends IndexClusters> clusterer,
int window) |
IncrementalLifetimeSparseClusterer(SparseMatrixClusterer<? extends IndexClusters> clusterer,
int window,
double threshold,
int lifetime) |
IncrementalLifetimeSparseClusterer(SparseMatrixClusterer<? extends IndexClusters> clusterer,
int window,
int lifetime) |
IncrementalSparseClusterer(SparseMatrixClusterer<? extends IndexClusters> clusterer,
int window) |
IncrementalSparseClusterer(SparseMatrixClusterer<? extends IndexClusters> clusterer,
int window,
double threshold) |
Modifier and Type | Class and Description |
---|---|
class |
RandomClusterer
Given a similarity or distance matrix, this clusterer randomly selects a
number of clusters and randomly assigned each row to each cluster.
|
Modifier and Type | Class and Description |
---|---|
class |
CachedDoubleSpectralClustering
DoubleSpectralClustering extention which knows how to write and read its eigenvectors to disk
and therefore not regenerate them when calling the underlying PreparedSpectralClustering |
class |
DoubleSpectralClustering
Built from a mixture of this tutorial:
- http://www.kyb.mpg.de/fileadmin/user_upload/files/publications/attachments/Luxburg07_tutorial_4488%5B0%5D.pdf
And this implementation:
- https://github.com/peterklipfel/AutoponicsVision/blob/master/SpectralClustering.java
|