Imran Younus created SYSTEMML-1238:
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Summary: 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
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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