GitHub user yanboliang opened a pull request:
https://github.com/apache/spark/pull/14378
[SPARK-16750] [ML] Fix GaussianMixture training failed due to feature
column type mistake
## What changes were proposed in this pull request?
ML ```GaussianMixture``` training failed due to feature column type
mistake. The feature column type should be ```ml.linalg.VectorUDT``` but got
```mllib.linalg.VectorUDT``` by mistake.
See [SPARK-16750](https://issues.apache.org/jira/browse/SPARK-16750) for
how to reproduce this bug.
Why the unit tests did not complain this errors? Because some
estimators/transformers missed calling ```transformSchema(dataset.schema)```
firstly during fit or transform. I will also add this function to all
estimators/transformers who missed in this PR.
## How was this patch tested?
No new tests, should pass existing ones.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/yanboliang/spark spark-16750
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14378.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 #14378
----
commit a0a32efa47be7dc0a51b71790bbee07620bb7d28
Author: Yanbo Liang <[email protected]>
Date: 2016-07-27T09:49:52Z
Fix GaussianMixture training failed due to feature column type mistake
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