From f3480440e7b7ac590f710709ca6ca0e13399ca11 Mon Sep 17 00:00:00 2001
From: Yuhao Yang <hhbyyh@gmail.com>
Date: Wed, 16 Mar 2016 16:17:04 -0700
Subject: [PATCH] revert some unintentional comment change

---
 .../GeneralizedLinearRegression.scala         | 40 ++++++-------------
 1 file changed, 13 insertions(+), 27 deletions(-)

diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
index f7a1c0e04857a..46ba5589ff85f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
@@ -46,7 +46,6 @@ private[regression] trait GeneralizedLinearRegressionBase extends PredictorParam
    * to be used in the model.
    * Supported options: "gaussian", "binomial", "poisson" and "gamma".
    * Default is "gaussian".
-   *
    * @group param
    */
   @Since("2.0.0")
@@ -63,8 +62,7 @@ private[regression] trait GeneralizedLinearRegressionBase extends PredictorParam
    * Param for the name of link function which provides the relationship
    * between the linear predictor and the mean of the distribution function.
    * Supported options: "identity", "log", "inverse", "logit", "probit", "cloglog" and "sqrt".
-    *
-    * @group param
+   * @group param
    */
   @Since("2.0.0")
   final val link: Param[String] = new Param(this, "link", "The name of link function " +
@@ -124,8 +122,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
   /**
    * Sets the value of param [[family]].
    * Default is "gaussian".
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setFamily(value: String): this.type = set(family, value)
@@ -133,8 +130,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
 
   /**
    * Sets the value of param [[link]].
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setLink(value: String): this.type = set(link, value)
@@ -142,8 +138,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
   /**
    * Sets if we should fit the intercept.
    * Default is true.
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setFitIntercept(value: Boolean): this.type = set(fitIntercept, value)
@@ -151,8 +146,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
   /**
    * Sets the maximum number of iterations.
    * Default is 25 if the solver algorithm is "irls".
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setMaxIter(value: Int): this.type = set(maxIter, value)
@@ -161,8 +155,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
    * Sets the convergence tolerance of iterations.
    * Smaller value will lead to higher accuracy with the cost of more iterations.
    * Default is 1E-6.
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setTol(value: Double): this.type = set(tol, value)
@@ -171,8 +164,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
   /**
    * Sets the regularization parameter.
    * Default is 0.0.
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setRegParam(value: Double): this.type = set(regParam, value)
@@ -182,8 +174,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
    * Sets the value of param [[weightCol]].
    * If this is not set or empty, we treat all instance weights as 1.0.
    * Default is empty, so all instances have weight one.
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setWeightCol(value: String): this.type = set(weightCol, value)
@@ -192,8 +183,7 @@ class GeneralizedLinearRegression @Since("2.0.0") (@Since("2.0.0") override val
   /**
    * Sets the solver algorithm used for optimization.
    * Currently only support "irls" which is also the default solver.
-    *
-    * @group setParam
+   * @group setParam
    */
   @Since("2.0.0")
   def setSolver(value: String): this.type = set(solver, value)
@@ -337,8 +327,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
 
   /**
    * A description of the error distribution to be used in the model.
-    *
-    * @param name the name of the family.
+   * @param name the name of the family.
    */
   private[ml] abstract class Family(val name: String) extends Serializable {
 
@@ -375,8 +364,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
 
     /**
      * Gets the [[Family]] object from its name.
-      *
-      * @param name family name: "gaussian", "binomial", "poisson" or "gamma".
+     * @param name family name: "gaussian", "binomial", "poisson" or "gamma".
      */
     def fromName(name: String): Family = {
       name match {
@@ -555,8 +543,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
    * A description of the link function to be used in the model.
    * The link function provides the relationship between the linear predictor
    * and the mean of the distribution function.
-    *
-    * @param name the name of link function.
+   * @param name the name of link function.
    */
   private[ml] abstract class Link(val name: String) extends Serializable {
 
@@ -574,8 +561,7 @@ object GeneralizedLinearRegression extends DefaultParamsReadable[GeneralizedLine
 
     /**
      * Gets the [[Link]] object from its name.
-      *
-      * @param name link name: "identity", "logit", "log",
+     * @param name link name: "identity", "logit", "log",
      *             "inverse", "probit", "cloglog" or "sqrt".
      */
     def fromName(name: String): Link = {