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| author | Zheng RuiFeng <ruifengz@foxmail.com> | 2016-11-15 15:44:50 +0100 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-11-15 15:44:50 +0100 |
| commit | 33be4da5391b884191c405ffbce7d382ea8a2f66 (patch) | |
| tree | 8605ef86a9b4077b5d23d3bfeb2d1de975d2005d /docs/mllib-clustering.md | |
| parent | d89bfc92302424406847ac7a9cfca714e6b742fc (diff) | |
| download | spark-33be4da5391b884191c405ffbce7d382ea8a2f66.tar.gz spark-33be4da5391b884191c405ffbce7d382ea8a2f66.tar.bz2 spark-33be4da5391b884191c405ffbce7d382ea8a2f66.zip | |
[SPARK-18427][DOC] Update docs of mllib.KMeans
## What changes were proposed in this pull request?
1,Remove `runs` from docs of mllib.KMeans
2,Add notes for `k` according to comments in sources
## How was this patch tested?
existing tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #15873 from zhengruifeng/update_doc_mllib_kmeans.
Diffstat (limited to 'docs/mllib-clustering.md')
| -rw-r--r-- | docs/mllib-clustering.md | 6 |
1 files changed, 2 insertions, 4 deletions
diff --git a/docs/mllib-clustering.md b/docs/mllib-clustering.md index d5f6ae379a..8990e95796 100644 --- a/docs/mllib-clustering.md +++ b/docs/mllib-clustering.md @@ -24,13 +24,11 @@ variant of the [k-means++](http://en.wikipedia.org/wiki/K-means%2B%2B) method called [kmeans||](http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf). The implementation in `spark.mllib` has the following parameters: -* *k* is the number of desired clusters. +* *k* is the number of desired clusters. Note that it is possible for fewer than k clusters to be returned, for example, if there are fewer than k distinct points to cluster. * *maxIterations* is the maximum number of iterations to run. * *initializationMode* specifies either random initialization or initialization via k-means\|\|. -* *runs* is the number of times to run the k-means algorithm (k-means is not -guaranteed to find a globally optimal solution, and when run multiple times on -a given dataset, the algorithm returns the best clustering result). +* *runs* This param has no effect since Spark 2.0.0. * *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. |