From f9c79b136ac41bd91f482a4f948acb780f493516 Mon Sep 17 00:00:00 2001
From: Yanbo Liang <ybliang8@gmail.com>
Date: Thu, 25 Feb 2016 17:35:57 +0800
Subject: [PATCH] ML LinearRegression should cache standardization param value

---
 .../org/apache/spark/ml/regression/LinearRegression.scala      | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
index e253f25c0ea65..ccfb5c4b9d697 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/LinearRegression.scala
@@ -277,8 +277,9 @@ class LinearRegression @Since("1.3.0") (@Since("1.3.0") override val uid: String
     val optimizer = if ($(elasticNetParam) == 0.0 || effectiveRegParam == 0.0) {
       new BreezeLBFGS[BDV[Double]]($(maxIter), 10, $(tol))
     } else {
+      val standardizationParam = $(standardization)
       def effectiveL1RegFun = (index: Int) => {
-        if ($(standardization)) {
+        if (standardizationParam) {
           effectiveL1RegParam
         } else {
           // If `standardization` is false, we still standardize the data