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https://issues.apache.org/jira/browse/SYSTEMML-1238?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Imran Younus reassigned SYSTEMML-1238:
--------------------------------------

    Assignee: Niketan Pansare

> Python test failing for LinearRegCG
> -----------------------------------
>
>                 Key: SYSTEMML-1238
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1238
>             Project: SystemML
>          Issue Type: Bug
>          Components: Algorithms, APIs
>    Affects Versions: SystemML 0.13
>            Reporter: Imran Younus
>            Assignee: Niketan Pansare
>         Attachments: python_LinearReg_test_spark.1.6.log, 
> python_LinearReg_test_spark.2.1.log
>
>
> [~deron] discovered that the one of the python test ({{test_mllearn_df.py}}) 
> with spark 2.1.0 was failing because the test score from linear regression 
> was very low ({{~ 0.24}}). I did a some investigation and it turns out the 
> the model parameters computed by the dml script are incorrect. In 
> systemml.12, the values of betas from linear regression model are 
> {{\[152.919, 938.237\]}}. This is what we expect from normal equation. (I 
> also tested this with sklearn). But the values of betas from systemml.13 
> (with spark 2.1.0) come out to be {{\[153.146, 458.489\]}}. These are not 
> correct and therefore the test score is much lower than expected. The data 
> going into DML script is correct. I printed out the valued of {{X}} and {{Y}} 
> in dml and I didn't see any issue there.
> Attached are the log files for two different tests (systemml0.12 and 0.13) 
> with explain flag.



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