Package | Description |
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weka.clusterers |
Modifier and Type | Class and Description |
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class |
Cobweb
Class implementing the Cobweb and Classit clustering algorithms.
Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers. |
class |
FarthestFirst
Cluster data using the FarthestFirst algorithm.
For more information see: Hochbaum, Shmoys (1985). |
class |
sIB
Cluster data using the sequential information bottleneck algorithm.
Note: only hard clustering scheme is supported. |
class |
SimpleKMeans
Cluster data using the k means algorithm
Valid options are:
|
class |
XMeans
Cluster data using the X-means algorithm.
X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted to be split in its region. |
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