Github user holdenk commented on a diff in the pull request:

    https://github.com/apache/spark/pull/7875#discussion_r36150394
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala ---
    @@ -85,6 +85,18 @@ class LinearRegression(override val uid: String)
       setDefault(fitIntercept -> true)
     
       /**
    +   * Whether to standardize the training features before fitting the model.
    +   * The coefficients of models will be always returned on the original 
scale,
    +   * so it will be transparent for users. Note that when no regularization,
    +   * with or without standardization, the models should be always 
converged to
    +   * the same solution.
    +   * Default is true.
    +   * @group setParam
    +   */
    +  def setStandardization(value: Boolean): this.type = set(standardization, 
value)
    +  setDefault(standardization -> true)
    --- End diff --
    
    Yah I think it would be nice to just mention that while this is a new flag, 
the old default effectively had this flag on so don't worry (also maybe add a 
@since tag?)


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]

Reply via email to