GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/15413
[SPARK-17847] [ML] Copy GaussianMixture implementation from mllib to ml
## What changes were proposed in this pull request?
Copy ```GaussianMixture``` implementation from mllib to ml, then we can add
new features to it.
I left mllib ```GaussianMixture``` untouched, unlike some other algorithms
to wrap the ml implementation. For the following reasons:
* mllib ```GaussianMixture``` allow k == 1, but ml does not.
* mllib ```GaussianMixture``` supports setting initial model, but ml does
not support currently. (We will definitely add this feature for ml in the
future)
Meanwhile, we did some improvements to handle sparse data more efficiently.
I use ```ml.linalg``` as the underlying data structure rather than the old
breeze dense vector.
Todo:
- [ ] Performance test.
## How was this patch tested?
Existing tests and added new tests.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark spark-17847
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/15413.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #15413
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commit 5a8de4a7289700d20e240dcf82b61552c213dcf8
Author: Yanbo Liang <[email protected]>
Date: 2016-10-10T05:00:53Z
Copy GaussianMixture implementation from mllib to ml
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