Github user iyounus commented on a diff in the pull request:
https://github.com/apache/spark/pull/10384#discussion_r48199690
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/evaluation/RegressionMetrics.scala
---
@@ -31,13 +30,17 @@ import org.apache.spark.sql.DataFrame
*/
@Since("1.2.0")
class RegressionMetrics @Since("1.2.0") (
- predictionAndObservations: RDD[(Double, Double)]) extends Logging {
+ predictionAndObservations: RDD[(Double, Double)], isUnbiased: Boolean
= true)
--- End diff --
I've skimmed through some literature, and see that some authors call the
constant in regression as "bias term" but its not very common. So `isUnbiased`
may not be right choice for this variable. As @sethah pointed out,
`fitIntercept` is not applicable in other regression models. How about
`regThroughOrigin`?
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