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| author | Sean Owen <sowen@cloudera.com> | 2016-09-04 12:40:51 +0100 |
|---|---|---|
| committer | Sean Owen <sowen@cloudera.com> | 2016-09-04 12:40:51 +0100 |
| commit | cdeb97a8cd26e3282cc2a4f126242ed2199f3898 (patch) | |
| tree | 22bb93ee40ae08cb0f1928c7c2fdd535739ecd23 /sql | |
| parent | e75c162e9e510d74b07f28ccf6c7948ac317a7c6 (diff) | |
| download | spark-cdeb97a8cd26e3282cc2a4f126242ed2199f3898.tar.gz spark-cdeb97a8cd26e3282cc2a4f126242ed2199f3898.tar.bz2 spark-cdeb97a8cd26e3282cc2a4f126242ed2199f3898.zip | |
[SPARK-17311][MLLIB] Standardize Python-Java MLlib API to accept optional long seeds in all cases
## What changes were proposed in this pull request?
Related to https://github.com/apache/spark/pull/14524 -- just the 'fix' rather than a behavior change.
- PythonMLlibAPI methods that take a seed now always take a `java.lang.Long` consistently, allowing the Python API to specify "no seed"
- .mllib's Word2VecModel seemed to be an odd man out in .mllib in that it picked its own random seed. Instead it defaults to None, meaning, letting the Scala implementation pick a seed
- BisectingKMeansModel arguably should not hard-code a seed for consistency with .mllib, I think. However I left it.
## How was this patch tested?
Existing tests
Author: Sean Owen <sowen@cloudera.com>
Closes #14826 from srowen/SPARK-16832.2.
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