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Diffstat (limited to 'docs/mllib-clustering.md')
| -rw-r--r-- | docs/mllib-clustering.md | 1 |
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diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md index d72dc20a5a..0fc7036bff 100644 --- a/docs/mllib-clustering.md +++ b/docs/mllib-clustering.md @@ -33,6 +33,7 @@ guaranteed to find a globally optimal solution, and when run multiple times on a given dataset, the algorithm returns the best clustering result). * *initializationSteps* determines the number of steps in the k-means\|\| algorithm. * *epsilon* determines the distance threshold within which we consider k-means to have converged. +* *initialModel* is an optional set of cluster centers used for initialization. If this parameter is supplied, only one run is performed. **Examples** |