Base classes parameters for computing initial centroids for K-Means algorithm.
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def __init__ |
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- Variant 1
Parameter constructor
- Parameters
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_nClusters | Number of clusters |
_offset | Offset in the total data set specifying the start of a block stored on a given local node |
_seed | Seed for generating random numbers for the initialization |
- Deprecated:
- This item will be removed in a future release. Use engine instead.
- Variant 2
Constructs parameters of the algorithm that computes initial centroids for K-Means algorithm by copying another parameters object
- Parameters
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other | Parameters of K-Means algorithm |
check(interface1_Parameter self) -> Status
Engine to be used for generating random numbers for the initialization
L = nClusters*oversamplingFactorpointsaresampledinaround. |
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Kmeans|| only. A fraction of nClusters being chosen in each of nRounds of kmeans||.
Kmeans|| only. Number of rounds for k-means||. (oversamplingFactor*nRounds) > 1 is a requirement.
Total number of rows in the data set
Offset in the total data set specifying the start of a block stored on a given local node
Seed for generating random numbers for the initialization
- Deprecated:
- This item will be removed in a future release.
Use engine instead.
The documentation for this class was generated from the following file: