1 files changed, 9 insertions, 6 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
index 2360f4479f..c865eb9fe0 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala
@@ -20,12 +20,13 @@ package org.apache.spark.ml.evaluation
 import org.apache.spark.annotation.AlphaComponent
 import org.apache.spark.ml.Evaluator
 import org.apache.spark.ml.param._
+import org.apache.spark.ml.param.shared._
+import org.apache.spark.ml.util.SchemaUtils
 import org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
 import org.apache.spark.mllib.linalg.{Vector, VectorUDT}
 import org.apache.spark.sql.{DataFrame, Row}
 import org.apache.spark.sql.types.DoubleType
 
-
 /**
  * :: AlphaComponent ::
  *
@@ -40,10 +41,10 @@ class BinaryClassificationEvaluator extends Evaluator with Params
    * @group param
    */
   val metricName: Param[String] = new Param(this, "metricName",
-    "metric name in evaluation (areaUnderROC|areaUnderPR)", Some("areaUnderROC"))
+    "metric name in evaluation (areaUnderROC|areaUnderPR)")
 
   /** @group getParam */
-  def getMetricName: String = get(metricName)
+  def getMetricName: String = getOrDefault(metricName)
 
   /** @group setParam */
   def setMetricName(value: String): this.type = set(metricName, value)
@@ -54,12 +55,14 @@ class BinaryClassificationEvaluator extends Evaluator with Params
   /** @group setParam */
   def setLabelCol(value: String): this.type = set(labelCol, value)
 
+  setDefault(metricName -> "areaUnderROC")
+
   override def evaluate(dataset: DataFrame, paramMap: ParamMap): Double = {
-    val map = this.paramMap ++ paramMap
+    val map = extractParamMap(paramMap)
 
     val schema = dataset.schema
-    checkInputColumn(schema, map(rawPredictionCol), new VectorUDT)
-    checkInputColumn(schema, map(labelCol), DoubleType)
+    SchemaUtils.checkColumnType(schema, map(rawPredictionCol), new VectorUDT)
+    SchemaUtils.checkColumnType(schema, map(labelCol), DoubleType)
 
     // TODO: When dataset metadata has been implemented, check rawPredictionCol vector length = 2.
     val scoreAndLabels = dataset.select(map(rawPredictionCol), map(labelCol))