[
https://issues.apache.org/jira/browse/SPARK-1945?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14047018#comment-14047018
]
Michael Yannakopoulos commented on SPARK-1945:
----------------------------------------------
Hi guys,
I have a difficulty transforming the code snippet provided for SVMWithSGD
[http://spark.apache.org/docs/latest/mllib-linear-methods.html#linear-support-vector-machine-svm]
to Java.
More specifically, I cannot figure out what type of parameters are accepted by
the _constructor_ of *BinaryClassificationMetrics*.
>From the ScalaDoc
>[http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.mllib.evaluation.BinaryClassificationMetrics],
>
I see that the constructor need to take an argument of type RDD[(Double,
Double)] which I suspect that translates into
JavaRDD<Tuple2<Double, Double>> or JavaRDD<Product2<Double, Double>> or
JavaRDD<Product<Double, Double>>.
However none of the above seem to work. Any suggestions?
> Add full Java examples in MLlib docs
> ------------------------------------
>
> Key: SPARK-1945
> URL: https://issues.apache.org/jira/browse/SPARK-1945
> Project: Spark
> Issue Type: Sub-task
> Components: Documentation, MLlib
> Reporter: Matei Zaharia
> Labels: Starter
> Fix For: 1.0.0
>
>
> Right now some of the Java tabs only say the following:
> "All of MLlib’s methods use Java-friendly types, so you can import and call
> them there the same way you do in Scala. The only caveat is that the methods
> take Scala RDD objects, while the Spark Java API uses a separate JavaRDD
> class. You can convert a Java RDD to a Scala one by calling .rdd() on your
> JavaRDD object."
> Would be nice to translate the Scala code into Java instead.
> Also, a few pages (most notably the Matrix one) don't have Java examples at
> all.
--
This message was sent by Atlassian JIRA
(v6.2#6252)
