2 files changed, 13 insertions, 0 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala
index b9b54b93c2..5b5a2a1450 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/evaluation/RankingMetrics.scala
@@ -31,6 +31,8 @@ import org.apache.spark.rdd.RDD
  * ::Experimental::
  * Evaluator for ranking algorithms.
  *
+ * Java users should use [[RankingMetrics$.of]] to create a [[RankingMetrics]] instance.
+ *
  * @param predictionAndLabels an RDD of (predicted ranking, ground truth set) pairs.
  */
 @Experimental
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
index 354e90f3ee..5e882d4ebb 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/pmml/PMMLExportable.scala
@@ -23,13 +23,16 @@ import javax.xml.transform.stream.StreamResult
 import org.jpmml.model.JAXBUtil
 
 import org.apache.spark.SparkContext
+import org.apache.spark.annotation.{DeveloperApi, Experimental}
 import org.apache.spark.mllib.pmml.export.PMMLModelExportFactory
 
 /**
+ * :: DeveloperApi ::
  * Export model to the PMML format
  * Predictive Model Markup Language (PMML) is an XML-based file format
  * developed by the Data Mining Group (www.dmg.org).
  */
+@DeveloperApi
 trait PMMLExportable {
 
   /**
@@ -41,30 +44,38 @@ trait PMMLExportable {
   }
 
   /**
+   * :: Experimental ::
    * Export the model to a local file in PMML format
    */
+  @Experimental
   def toPMML(localPath: String): Unit = {
     toPMML(new StreamResult(new File(localPath)))
   }
 
   /**
+   * :: Experimental ::
    * Export the model to a directory on a distributed file system in PMML format
    */
+  @Experimental
   def toPMML(sc: SparkContext, path: String): Unit = {
     val pmml = toPMML()
     sc.parallelize(Array(pmml), 1).saveAsTextFile(path)
   }
 
   /**
+   * :: Experimental ::
    * Export the model to the OutputStream in PMML format
    */
+  @Experimental
   def toPMML(outputStream: OutputStream): Unit = {
     toPMML(new StreamResult(outputStream))
   }
 
   /**
+   * :: Experimental ::
    * Export the model to a String in PMML format
    */
+  @Experimental
   def toPMML(): String = {
     val writer = new StringWriter
     toPMML(new StreamResult(writer))