[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15327205#comment-15327205 ] Villu Ruusmann commented on SPARK-8546: --- Hi [~rgasiorek] - would it be an option to re-build your models in Spark ML instead of MLlib? I have been working on Spark ML pipelines-to-PMML converter called JPMML-SparkML (https://github.com/jpmml/jpmml-sparkml), which could fully address your use case then. JPMML-SparkML supports all tree-based models and the majority of non-NLP domain transformations. It would be possible to add support for the `classification.NaiveBayesModel` model type in a day or two if needed. > PMML export for Naive Bayes > --- > > Key: SPARK-8546 > URL: https://issues.apache.org/jira/browse/SPARK-8546 > Project: Spark > Issue Type: New Feature > Components: MLlib >Reporter: Joseph K. Bradley >Assignee: Xusen Yin >Priority: Minor > > The naive Bayes section of PMML standard can be found at > http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to > generate PMML for both binomial and multinomial naive Bayes models using > JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15327167#comment-15327167 ] Radoslaw Gasiorek commented on SPARK-8546: -- hi there, [~josephkb] We would like to use Mllib built models to classify outside spark therefore without Spark context available. We would like to export the models built in spark into PMML format, that then would be read by a stand alone java application without spark context (but with Mllib jar). The java application would load the model from the PMML file and would use the model to 'predict' or rather 'classify' the new data we get. This feature would enable us to proceed without big architectural and operational changes, without this feature we might need get the the sparkContext available to the standalone application that would be bigger operational and architectural overhead. We might need to use the plain java serialization for the proof of concept anyways, but surely not for produtionized product. Can we prioritize this feature as well as https://issues.apache.org/jira/browse/SPARK-8542 and https://issues.apache.org/jira/browse/SPARK-8543 ? What would be LOE and EAT for these? thanks guys in advance for responses, and feedback. > PMML export for Naive Bayes > --- > > Key: SPARK-8546 > URL: https://issues.apache.org/jira/browse/SPARK-8546 > Project: Spark > Issue Type: New Feature > Components: MLlib >Reporter: Joseph K. Bradley >Assignee: Xusen Yin >Priority: Minor > > The naive Bayes section of PMML standard can be found at > http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to > generate PMML for both binomial and multinomial naive Bayes models using > JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15258889#comment-15258889 ] Joseph K. Bradley commented on SPARK-8546: -- I'm removing the target version. It will be good to add but will slip for 2.0 > PMML export for Naive Bayes > --- > > Key: SPARK-8546 > URL: https://issues.apache.org/jira/browse/SPARK-8546 > Project: Spark > Issue Type: New Feature > Components: MLlib >Reporter: Joseph K. Bradley >Assignee: Xusen Yin >Priority: Minor > > The naive Bayes section of PMML standard can be found at > http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to > generate PMML for both binomial and multinomial naive Bayes models using > JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14951018#comment-14951018 ] Xiangrui Meng commented on SPARK-8546: -- Assigned. Thanks! > PMML export for Naive Bayes > --- > > Key: SPARK-8546 > URL: https://issues.apache.org/jira/browse/SPARK-8546 > Project: Spark > Issue Type: New Feature > Components: MLlib >Reporter: Joseph K. Bradley >Assignee: Xusen Yin >Priority: Minor > > The naive Bayes section of PMML standard can be found at > http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to > generate PMML for both binomial and multinomial naive Bayes models using > JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14949361#comment-14949361 ] Xusen Yin commented on SPARK-8546: -- Hi [~mengxr], I'd like to work on it. > PMML export for Naive Bayes > --- > > Key: SPARK-8546 > URL: https://issues.apache.org/jira/browse/SPARK-8546 > Project: Spark > Issue Type: New Feature > Components: MLlib >Reporter: Joseph K. Bradley >Priority: Minor > > The naive Bayes section of PMML standard can be found at > http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to > generate PMML for both binomial and multinomial naive Bayes models using > JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-8546) PMML export for Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-8546?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14602023#comment-14602023 ] Villu Ruusmann commented on SPARK-8546: --- The NB exporter should be easier to implement than Logistic regression and SVM exporters, because the PMML representation of NB models does not distinguish between binary and multi-class classification cases. I'm currently developing PMML exporters for the Python ML module called Scikit-Learn. Unfortunately, I haven't made to Scikit-Learn classes GaussianNB and MultinomialNB yet. I shall be much wiser once I get them done. PMML export for Naive Bayes --- Key: SPARK-8546 URL: https://issues.apache.org/jira/browse/SPARK-8546 Project: Spark Issue Type: New Feature Components: MLlib Reporter: Joseph K. Bradley Priority: Minor The naive Bayes section of PMML standard can be found at http://www.dmg.org/v4-1/NaiveBayes.html. We should first figure out how to generate PMML for both binomial and multinomial naive Bayes models using JPMML (maybe [~vfed] can help). -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
