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https://issues.apache.org/jira/browse/SPARK-8335?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14591357#comment-14591357
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Sean Owen commented on SPARK-8335:
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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].
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