GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/16131
[SPARK-18701][ML] Poisson GLM fails due to wrong initialization
Poisson GLM fails for many standard data sets (see example in test or
JIRA). The issue is incorrect initialization leading to almost zero probability
and weights. Specifically, the mean is initialized as the response, which could
be zero. Applying the log link results in very negative numbers (protected
against -Inf), which again leads to close to zero probability and weights in
the weighted least squares. Fix and test are included in the commits.
## What changes were proposed in this pull request?
Update initialization in Poisson GLM
## How was this patch tested?
Add test in GeneralizedLinearRegressionSuite
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/actuaryzhang/spark master
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/16131.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 #16131
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commit 784cb09343bb1bae50c23dd943acf11a4baded03
Author: actuaryzhang <actuaryzhan...@gmail.com>
Date: 2016-12-04T00:41:29Z
Change initial value in Poisson GLM to avoid numerical issue
commit 56c4779a5e0f7de902aa22c943192500b6c85c37
Author: actuaryzhang <actuaryzhan...@gmail.com>
Date: 2016-12-04T03:06:53Z
Update Poisson GLM test (for incorrect initialization)
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