Github user iyounus commented on a diff in the pull request: https://github.com/apache/spark/pull/10384#discussion_r48287387 --- Diff: mllib/src/main/scala/org/apache/spark/mllib/evaluation/RegressionMetrics.scala --- @@ -23,15 +23,23 @@ import org.apache.spark.Logging import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.stat.{MultivariateStatisticalSummary, MultivariateOnlineSummarizer} import org.apache.spark.sql.DataFrame - /** * Evaluator for regression. * - * @param predictionAndObservations an RDD of (prediction, observation) pairs. + * @param predictionAndObservations an RDD of (prediction, observation) pairs, + * @param regThroughOrigin true if intercept is not included in linear regression model --- End diff -- Both have pros and cons. I'm not sure which one is better from user's perspective (who is not reading the code). Personally, I would prefer `hasFitIntercept` to be consistent with the code. I can make this change if we can reach consensus.
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