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I can answer the first question from just referring to the doc:
1. What is a meaning of "number of clusters" for both algorithms ?
For OC it seems to be a max possible value, while for KM value to fit.
How to predict "proper" number of clusters for data (especially for KM)?
Maximum number of leaf clusters generated by a clustering algorithm.
(Oracle Data Mining clustering algorithms are hierarchical)
Enhanced k-Means usually produces the exact number of clusters specified by CLUS_NUM_CLUSTERS, unless there are fewer distinct data points.
O-Cluster may produce fewer clusters than the number specified by CLUS_NUM_CLUSTERS, depending on the data.
2. Where can I find some more informations about coefficients of algorithms ?
But not what they are, but what are consequences of changing default values for algorithms
(e.g what will be a consequence for changing convergence tollerance for KM from 0,1 to 0,2) ??
Answer: The documentation does not always get into the details of the impact of changing a specific setting.
I will see if I can get some further information from the developer.
virtual api book: