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https://issues.apache.org/jira/browse/MADLIB-1094?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16131324#comment-16131324
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Frank McQuillan commented on MADLIB-1094:
-----------------------------------------
this works now
{code}
DROP TABLE IF EXISTS house_en,house_en_summary;
SELECT madlib.elastic_net_train(
'houses', -- input
'house_en', -- ouput
'price', -- dependent var
'ARRAY[tax, bath, size]', -- independent vars
'gaussian', -- regression family
0.5, -- alpha
0.5, -- lambda
True, -- normalize?
NULL, -- grouping col
'igd', -- optimizer
'', -- optimizer params
NULL, -- excluded cols
1, -- max iterations
1e-6 -- tolerance
{code}
> 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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