Hello, I would like to use other metrics in BinaryClassificaitonEvaluator, I am thinking about simple ones (i.e. PrecisionByThreshold). From the api site, I can't tell much about how to implement it.
>From the code, it seems like I will have to override this function, using most of the existing code for checking column schema, then replace the line which compute the actual score <https://github.com/apache/spark/blob/1b8625f4258d6d1a049d0ba60e39e9757f5a568b/mllib/src/main/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluator.scala#L72> . Is my understanding correct? Or there are more convenient way of implementing a metric in order to be used by ML pipeline? Thanks. Justin -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Implementing-custom-metrics-under-MLPipeline-s-BinaryClassificationEvaluator-tp22930.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
