Methods of computing initial clusters for the K-Means algorithm.
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◆ InitMethod()
Constructs the initialization method object using the provided value
- Parameters
-
value | Value corresponding to the initialization method object |
◆ getValue()
Returns the value corresponding to the initialization method object
- Returns
- Value corresponding to the initialization method object
◆ defaultDense
Default: uses first nClusters points as initial clusters
◆ deterministicCSR
Uses first nClusters points as initial clusters for data in a CSR numeric table
◆ deterministicDense
Synonym of deterministicDense
◆ parallelPlusCSR
Kmeans|| algorithm: scalable Kmeans++ by Bahmani et al. (2012)
◆ parallelPlusDense
Kmeans|| algorithm: scalable Kmeans++ by Bahmani et al. (2012)
◆ plusPlusCSR
Kmeans++ algorithm by Arthur and Vassilvitskii (2007)
◆ plusPlusDense
Kmeans++ algorithm by Arthur and Vassilvitskii (2007)
◆ randomCSR
Uses random nClusters points as initial clusters for data in a CSR numeric table
◆ randomDense
Uses random nClusters points as initial clusters
The documentation for this class was generated from the following file:
- kmeans/init/InitMethod.java