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Github user yinxusen commented on the pull request:
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retest this please
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Github user yinxusen commented on the pull request:
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@mengxr @selvinsource As we talked there, I don't think PMML has good
supports for multinomial naive bayes because we cannot fit the model of
multinomial naive bayes
Github user yinxusen commented on the pull request:
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@mengxr How do you think about the PMML export for Multinomial Naive Bayes?
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Github user selvinsource commented on the pull request:
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@yinxusen
https://github.com/selvinsource/spark-pmml-exporter-validator/tree/logistic_regression_multi_class
I tested both multinomial and bernoulli.
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Github user yinxusen commented on the pull request:
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If you want to see the exported xml of multinomial distribution, click
Github user selvinsource commented on the pull request:
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@yinxusen I will check out your branch and do some testing as well using
the validator.
From what I can see the exported xml seems correct :+1: .
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Github user yinxusen commented on the pull request:
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@selvinsource Yes I looks correct and the same with what I exported from R
(with libraries pmml and e1071 for naive bayes). But I am a little worried
about the
Github user yinxusen commented on the pull request:
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@selvinsource @mengxr I modified your [code of pmml export
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Github user selvinsource commented on the pull request:
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@yinxusen for multinomial naive Bayes you could still use the inputs as
discrete as they should be frequency of the terms accordingly to the
documentation,
Github user yinxusen commented on the pull request:
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@selvinsource Sorry for taking too long a time. I check the code and
generated XML file carefully. The null pointer is caused by a mistake that I
process continuous
Github user yinxusen commented on the pull request:
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@selvinsource I"ll check it ASAP. Thanks!
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Github user selvinsource commented on the pull request:
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@yinxusen
If you look at
https://github.com/selvinsource/spark-pmml-exporter-validator/tree/logistic_regression_multi_class
I added a test for your
Github user vruusmann commented on the pull request:
https://github.com/apache/spark/pull/9057#issuecomment-152766778
You may want to check out some valid NaiveBayes models. For example, see
the following NB model for the popular "Audit" dataset:
Github user vruusmann commented on the pull request:
https://github.com/apache/spark/pull/9057#issuecomment-15273
The value of the `TargetValueCount@value` attribute must equal some
**valid** value of the target `DataField` element (as defined by
`DataField/Value@value`
Github user selvinsource commented on the pull request:
https://github.com/apache/spark/pull/9057#issuecomment-152173191
@JasmineGeorge, it would be great if you can add a test for the validator
to ensure the exported xml file can be loaded in JPMML and score the same
results.
Github user JasmineGeorge commented on the pull request:
https://github.com/apache/spark/pull/9057#issuecomment-152181045
Sorry I can't get to it until next Wednesday.. Can someone else take over
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Github user selvinsource commented on the pull request:
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I will do it, no prob.
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Github user mengxr commented on the pull request:
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@JasmineGeorge Please sign off if the changes look good to you:)
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