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Posted to commits@spark.apache.org by me...@apache.org on 2014/09/04 05:47:07 UTC
git commit: [SPARK-3372] [MLlib] MLlib doesn't pass maven build /
checkstyle due to multi-byte character contained in Gradient.scala
Repository: spark
Updated Branches:
refs/heads/master 7c6e71f05 -> 1bed0a386
[SPARK-3372] [MLlib] MLlib doesn't pass maven build / checkstyle due to multi-byte character contained in Gradient.scala
Author: Kousuke Saruta <sa...@oss.nttdata.co.jp>
Closes #2248 from sarutak/SPARK-3372 and squashes the following commits:
73a28b8 [Kousuke Saruta] Replaced UTF-8 hyphen with ascii hyphen
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/1bed0a38
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/1bed0a38
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/1bed0a38
Branch: refs/heads/master
Commit: 1bed0a3869a526241381d2a74ba064e5b3721336
Parents: 7c6e71f
Author: Kousuke Saruta <sa...@oss.nttdata.co.jp>
Authored: Wed Sep 3 20:47:00 2014 -0700
Committer: Xiangrui Meng <me...@databricks.com>
Committed: Wed Sep 3 20:47:00 2014 -0700
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.../scala/org/apache/spark/mllib/optimization/Gradient.scala | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
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http://git-wip-us.apache.org/repos/asf/spark/blob/1bed0a38/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
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diff --git a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
index fdd6716..45dbf60 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/optimization/Gradient.scala
@@ -128,7 +128,7 @@ class LeastSquaresGradient extends Gradient {
class HingeGradient extends Gradient {
override def compute(data: Vector, label: Double, weights: Vector): (Vector, Double) = {
val dotProduct = dot(data, weights)
- // Our loss function with {0, 1} labels is max(0, 1 - (2y – 1) (f_w(x)))
+ // Our loss function with {0, 1} labels is max(0, 1 - (2y - 1) (f_w(x)))
// Therefore the gradient is -(2y - 1)*x
val labelScaled = 2 * label - 1.0
if (1.0 > labelScaled * dotProduct) {
@@ -146,7 +146,7 @@ class HingeGradient extends Gradient {
weights: Vector,
cumGradient: Vector): Double = {
val dotProduct = dot(data, weights)
- // Our loss function with {0, 1} labels is max(0, 1 - (2y – 1) (f_w(x)))
+ // Our loss function with {0, 1} labels is max(0, 1 - (2y - 1) (f_w(x)))
// Therefore the gradient is -(2y - 1)*x
val labelScaled = 2 * label - 1.0
if (1.0 > labelScaled * dotProduct) {
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