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https://issues.apache.org/jira/browse/MADLIB-1094?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16122503#comment-16122503
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ASF GitHub Bot commented on MADLIB-1094:
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GitHub user cooper-sloan opened a pull request:
https://github.com/apache/incubator-madlib/pull/164
Elastic Net: Fix normalization issue
MADLIB-1094 and MADLIB-1146
avg in psql is numerically unstable
Data scaling was not occuring when
grouping is true.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/cooper-sloan/incubator-madlib
elastic_net_normalization
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-madlib/pull/164.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 #164
----
commit 0b00513bf20e7f0b9032b267472321bd6cfc4355
Author: Cooper Sloan <[email protected]>
Date: 2017-08-10T19:04:04Z
Elastic Net: Fix normalization issue
MADLIB-1094 and MADLIB-1146
avg in psql is numerically unstable
Data scaling was not occuring when
grouping is true.
----
> Elastic Net fails when used without normalization
> -------------------------------------------------
>
> Key: MADLIB-1094
> URL: https://issues.apache.org/jira/browse/MADLIB-1094
> Project: Apache MADlib
> Issue Type: Bug
> Components: Module: Regularized Regression
> Reporter: Nandish Jayaram
> Priority: Minor
> Fix For: v1.12
>
>
> Using Elastic Net with the normalization/standardize flag turned off (for
> Gaussian IGD) results in failure, with the following error:
> {code:sql}
> madlib-pg94=# SELECT madlib.elastic_net_train(
> 'houses1',
> 'houses_en',
> 'array[tax, bath, size]',
> 'gaussian',
> 0.5,
> 0.1,
> FALSE, -- Standardize
> NULL,
> 'igd',
> '',
> NULL,
> 10000,1e-6);
> ERROR: spiexceptions.NumericValueOutOfRange: value out of range: overflow
> CONTEXT: Traceback (most recent call last):
> PL/Python function "elastic_net_train", line 23, in <module>
> return elastic_net.elastic_net_train(**globals())
> PL/Python function "elastic_net_train", line 332, in elastic_net_train
> PL/Python function "elastic_net_train", line 42, in
> __elastic_net_gaussian_igd_train
> PL/Python function "elastic_net_train", line 268, in __elastic_net_igd_train
> PL/Python function "elastic_net_train", line 373, in
> __elastic_net_igd_train_compute
> PL/Python function "elastic_net_train", line 69, in
> __elastic_net_generate_result
> PL/Python function "elastic_net_train", line 154, in
> __compute_log_likelihood
> PL/Python function "elastic_net_train"
> {code}
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