Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/8290#discussion_r37424665
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/evaluation/Evaluator.scala ---
@@ -46,5 +46,12 @@ abstract class Evaluator extends Params {
*/
def evaluate(dataset: DataFrame): Double
+ /**
+ * Indicates whether the metric returned by [[evaluate()]] should be
maximized (true)
+ * or minimized (false).
+ * A given evaluator may support multiple metrics which may be maximized
or minimized.
+ */
+ def shouldMaximize: Boolean
--- End diff --
* `Evaluator` reports the metrics but not maximizes them. I would suggest
`isLargerBetter` instead.
* This is a break change if we don't put a default value. I would suggest a
default value `true` to keep it consistent with implementations in Spark 1.4.
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