[jira] [Commented] (SPARK-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14592148#comment-14592148 ] Joseph K. Bradley commented on SPARK-8335: -- I agree we're too liberal with marking items as Experimental. In general, I hope we can mark major new items as Experimental for 1 release after they are first added, and then unmark them except in special cases. DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14591357#comment-14591357 ] Sean Owen commented on SPARK-8335: -- I don't feel strongly about it, but it is inconsistent with the same pattern in a few other classes. If we are allowed to fix the API and it's an easy fix, I figured, why not just fix it up for anyone that will use it for the rest of its lifetime? Or is the feeling that an API change, even where compatibility was not promised, just not worth it? this is a separate question from whether people should or would use a newer API. DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14591393#comment-14591393 ] Joseph K. Bradley commented on SPARK-8335: -- My initial thought was to fix it to make it consistent, but I was discouraged from making a breaking change for a nicety like this. I think Matei some of the original people in particular feel strongly about maintaining stable APIs as much as possible, even if items are marked as experimental/developer api. DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14590922#comment-14590922 ] Joseph K. Bradley commented on SPARK-8335: -- I've discussed this with [~mengxr] and we decided to leave it alone. I agree it's annoying, but we figured that people will use the Pipelines API in the future (where this is not an issue) and not breaking people's code would be best. Does that sound tolerable? DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14589492#comment-14589492 ] Apache Spark commented on SPARK-8335: - User 'srowen' has created a pull request for this issue: https://github.com/apache/spark/pull/6854 DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14586248#comment-14586248 ] Sebastian Walz commented on SPARK-8335: --- Yeah I am sure, that is a really a scala.Double. I just looked it up again on github. So the problem still exists in on the current master branch. DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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-8335) DecisionTreeModel.predict() return type not convenient!
[ https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14587013#comment-14587013 ] Sean Owen commented on SPARK-8335: -- Go ahead and propose a PR. The sticky issue here is whether it's ok to change an experimental API at this point. I think so. DecisionTreeModel.predict() return type not convenient! --- Key: SPARK-8335 URL: https://issues.apache.org/jira/browse/SPARK-8335 Project: Spark Issue Type: Bug Components: MLlib Affects Versions: 1.3.1 Reporter: Sebastian Walz Priority: Minor Labels: easyfix, machine_learning Original Estimate: 10m Remaining Estimate: 10m org.apache.spark.mllib.tree.model.DecisionTreeModel has a predict method: def predict(features: JavaRDD[Vector]): JavaRDD[Double] The problem here is the generic type of the return type JAVARDD[Double] because its a scala Double and I would expect a java.lang.Double. (to be convenient e.g. with org.apache.spark.mllib.classification.ClassificationModel) I wanted to extend the DecisionTreeModel and use it only for Binary Classification and wanted to implement the trait org.apache.spark.mllib.classification.ClassificationModel . But its not possible because the ClassificationModel already defines the predict method but with an return type JAVARDD[java.lang.Double]. -- 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
