[jira] [Commented] (SPARK-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14633641#comment-14633641 ] Apache Spark commented on SPARK-9112: - User 'MechCoder' has created a pull request for this issue: https://github.com/apache/spark/pull/7538 > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630541#comment-14630541 ] Joseph K. Bradley commented on SPARK-9112: -- Wrapping metrics is a reasonable start, and I'd like us to gradually add more capabilities. If we find we can share code between models, that's great too. > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630132#comment-14630132 ] Manoj Kumar commented on SPARK-9112: I see that these are fields in the transformed dataframe already (the raw predictions, probablity etc). I think just wrapping up the metrics should suffice. I'll send a PR in a while > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630053#comment-14630053 ] Manoj Kumar commented on SPARK-9112: Yes, that is the idea. Also we need not port it to ML right now, we could convert the transformed the dataframe to the required input type in mllib Also it might be useful to return the probability for the predicted class (as done by predict_proba in scikit-learn) . how does that sound? > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630028#comment-14630028 ] Sean Owen commented on SPARK-9112: -- LinearRegressionSummary wraps RegressionMetrics. Maybe it's best to follow a similar pattern porting BinaryClassificationMetrics to .ml and reusing that? > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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-9112) Implement LogisticRegressionSummary similar to LinearRegressionSummary
[ https://issues.apache.org/jira/browse/SPARK-9112?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14630014#comment-14630014 ] Manoj Kumar commented on SPARK-9112: Indeed, it seems so. But the merged LinearRegressionSummary also has just RegressionMetrics (unless there is anything that I missed.) By the way, I'm not sure how to set the priority labels, sorry if it is wrong (the umbrella JIRA has a critical priority, so I though that this might qualify as major) > Implement LogisticRegressionSummary similar to LinearRegressionSummary > -- > > Key: SPARK-9112 > URL: https://issues.apache.org/jira/browse/SPARK-9112 > Project: Spark > Issue Type: New Feature > Components: ML >Reporter: Manoj Kumar >Priority: Minor > > Since the API for LinearRegressionSummary has been merged, other models > should follow suit. -- 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
