[jira] [Commented] (SPARK-6164) CrossValidatorModel should keep stats from fitting
[ https://issues.apache.org/jira/browse/SPARK-6164?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14569714#comment-14569714 ] Leah McGuire commented on SPARK-6164: - I fixed the merge conflict. Should be good to go now. CrossValidatorModel should keep stats from fitting -- Key: SPARK-6164 URL: https://issues.apache.org/jira/browse/SPARK-6164 Project: Spark Issue Type: Improvement Components: ML Affects Versions: 1.4.0 Reporter: Joseph K. Bradley Priority: Minor CrossValidator computes stats for each (model, fold) pair, but they are thrown out by the created model. CrossValidatorModel should keep this info and expose it to users. -- 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-7545) Bernoulli NaiveBayes should validate data
[ https://issues.apache.org/jira/browse/SPARK-7545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14539078#comment-14539078 ] Leah McGuire commented on SPARK-7545: - Yes, I think I can get it in. Bernoulli NaiveBayes should validate data - Key: SPARK-7545 URL: https://issues.apache.org/jira/browse/SPARK-7545 Project: Spark Issue Type: Improvement Components: MLlib Affects Versions: 1.4.0 Reporter: Joseph K. Bradley Assignee: Leah McGuire Priority: Minor Bernoulli NaiveBayes expects input features to take values 0 or 1, but it does not actually check that. It should check and throw an exception if it finds invalid values. -- 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-7545) Bernoulli NaiveBayes should validate data
[ https://issues.apache.org/jira/browse/SPARK-7545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14539077#comment-14539077 ] Leah McGuire commented on SPARK-7545: - I think I can get it in :-) On Mon, May 11, 2015 at 4:45 PM, Joseph K. Bradley (JIRA) j...@apache.org Bernoulli NaiveBayes should validate data - Key: SPARK-7545 URL: https://issues.apache.org/jira/browse/SPARK-7545 Project: Spark Issue Type: Improvement Components: MLlib Affects Versions: 1.4.0 Reporter: Joseph K. Bradley Assignee: Leah McGuire Priority: Minor Bernoulli NaiveBayes expects input features to take values 0 or 1, but it does not actually check that. It should check and throw an exception if it finds invalid values. -- 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] [Issue Comment Deleted] (SPARK-7545) Bernoulli NaiveBayes should validate data
[ https://issues.apache.org/jira/browse/SPARK-7545?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Leah McGuire updated SPARK-7545: Comment: was deleted (was: Yes, I think I can get it in. ) Bernoulli NaiveBayes should validate data - Key: SPARK-7545 URL: https://issues.apache.org/jira/browse/SPARK-7545 Project: Spark Issue Type: Improvement Components: MLlib Affects Versions: 1.4.0 Reporter: Joseph K. Bradley Assignee: Leah McGuire Priority: Minor Bernoulli NaiveBayes expects input features to take values 0 or 1, but it does not actually check that. It should check and throw an exception if it finds invalid values. -- 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-6164) CrossValidatorModel should keep stats from fitting
[ https://issues.apache.org/jira/browse/SPARK-6164?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14529110#comment-14529110 ] Leah McGuire commented on SPARK-6164: - Closed this - accidentally pulled in pieces of another request CrossValidatorModel should keep stats from fitting -- Key: SPARK-6164 URL: https://issues.apache.org/jira/browse/SPARK-6164 Project: Spark Issue Type: Improvement Components: ML Affects Versions: 1.4.0 Reporter: Joseph K. Bradley Priority: Minor CrossValidator computes stats for each (model, fold) pair, but they are thrown out by the created model. CrossValidatorModel should keep this info and expose it to users. -- 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] [Created] (SPARK-5328) Update PySpark MLlib NaiveBayes API to take model type parameter for Bernoulli fit
Leah McGuire created SPARK-5328: --- Summary: Update PySpark MLlib NaiveBayes API to take model type parameter for Bernoulli fit Key: SPARK-5328 URL: https://issues.apache.org/jira/browse/SPARK-5328 Project: Spark Issue Type: Improvement Components: MLlib Reporter: Leah McGuire Priority: Minor [SPARK-4894] Add Bernoulli-variant of Naive Bayes adds Bernoulli fitting to NaiveBayes.scala need to update python API to accept model type parameter. -- 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] [Updated] (SPARK-5328) Update PySpark MLlib NaiveBayes API to take model type parameter for Bernoulli fit
[ https://issues.apache.org/jira/browse/SPARK-5328?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Leah McGuire updated SPARK-5328: Description: [SPARK-4894] Adds Bernoulli-variant of Naive Bayes adds Bernoulli fitting to NaiveBayes.scala need to update python API to accept model type parameter. (was: [SPARK-4894] Add Bernoulli-variant of Naive Bayes adds Bernoulli fitting to NaiveBayes.scala need to update python API to accept model type parameter.) Update PySpark MLlib NaiveBayes API to take model type parameter for Bernoulli fit -- Key: SPARK-5328 URL: https://issues.apache.org/jira/browse/SPARK-5328 Project: Spark Issue Type: Improvement Components: MLlib Reporter: Leah McGuire Priority: Minor Labels: mllib [SPARK-4894] Adds Bernoulli-variant of Naive Bayes adds Bernoulli fitting to NaiveBayes.scala need to update python API to accept model type parameter. -- 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-4894) Add Bernoulli-variant of Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-4894?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14281444#comment-14281444 ] Leah McGuire commented on SPARK-4894: - Hi [~rnowling], I submitted a pull request to add just the Bernoulli NB to the existing code. It follows the outline you suggested above with the exemption of the fact that I used an enumeration for the model type rather than a simple string. If you would have time to review it I would appreciate the feedback! Add Bernoulli-variant of Naive Bayes Key: SPARK-4894 URL: https://issues.apache.org/jira/browse/SPARK-4894 Project: Spark Issue Type: New Feature Components: MLlib Affects Versions: 1.2.0 Reporter: RJ Nowling Assignee: RJ Nowling MLlib only supports the multinomial-variant of Naive Bayes. The Bernoulli version of Naive Bayes is more useful for situations where the features are binary values. -- 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-4894) Add Bernoulli-variant of Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-4894?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14277590#comment-14277590 ] Leah McGuire commented on SPARK-4894: - Thanks [~rnowling]! I can take a look at it this week and at least confirm that the docs are incorrect and outline the changes that need to occur. If I have time I will try to send you a patch this week, if not I'm happy to help with review and testing for your patch. Add Bernoulli-variant of Naive Bayes Key: SPARK-4894 URL: https://issues.apache.org/jira/browse/SPARK-4894 Project: Spark Issue Type: New Feature Components: MLlib Affects Versions: 1.2.0 Reporter: RJ Nowling Assignee: RJ Nowling MLlib only supports the multinomial-variant of Naive Bayes. The Bernoulli version of Naive Bayes is more useful for situations where the features are binary values. -- 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-4894) Add Bernoulli-variant of Naive Bayes
[ https://issues.apache.org/jira/browse/SPARK-4894?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14276161#comment-14276161 ] Leah McGuire commented on SPARK-4894: - Are you guys working on this? I would like to contribute as well. Add Bernoulli-variant of Naive Bayes Key: SPARK-4894 URL: https://issues.apache.org/jira/browse/SPARK-4894 Project: Spark Issue Type: New Feature Components: MLlib Affects Versions: 1.1.1 Reporter: RJ Nowling MLlib only supports the multinomial-variant of Naive Bayes. The Bernoulli version of Naive Bayes is more useful for situations where the features are binary values. -- 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
