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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