GitHub user tengpeng opened a pull request:
https://github.com/apache/spark/pull/19660
[SPARK-18755][WIP][ML] Add Randomized Grid Search to Spark ML
## What changes were proposed in this pull request?
Python sklearn has a randomized grid search for reducing the time for
parameter tuning:
1. If the candidate parameter values are all discrete, sampling with
replacement.
2. If at least one candidate parameter is continuous, sampling without
replacement.
This patch mimic the behavior of case 1 only. If we want to do 2, we need
significant changes in `ParamGridBuilder` and other cross validation
components. This requires more discussions. Thoughts?
Reference:
http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html
## How was this patch tested?
Existing test + a new unit test.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/tengpeng/spark CV
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/19660.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 #19660
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commit 46086202f14185b18351f50c9c09f0641af4bb4f
Author: test <joseph.p...@quetica.com>
Date: 2017-11-05T22:40:51Z
Initial commit for searchRatio
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