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author | Xiangrui Meng <meng@databricks.com> | 2015-03-03 23:52:02 -0800 |
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committer | Xiangrui Meng <meng@databricks.com> | 2015-03-03 23:52:02 -0800 |
commit | 76e20a0a03cf2c02db35e00271924efb070eaaa5 (patch) | |
tree | 73c944fa1950db6eba7df0050e2be37c2c207a68 /mllib/src | |
parent | d334bfbcf38d0c1c6835e72bc85e42196e295744 (diff) | |
download | spark-76e20a0a03cf2c02db35e00271924efb070eaaa5.tar.gz spark-76e20a0a03cf2c02db35e00271924efb070eaaa5.tar.bz2 spark-76e20a0a03cf2c02db35e00271924efb070eaaa5.zip |
[SPARK-6141][MLlib] Upgrade Breeze from 0.10 to 0.11 to fix convergence bug
LBFGS and OWLQN in Breeze 0.10 has convergence check bug.
This is fixed in 0.11, see the description in Breeze project for detail:
https://github.com/scalanlp/breeze/pull/373#issuecomment-76879760
Author: Xiangrui Meng <meng@databricks.com>
Author: DB Tsai <dbtsai@alpinenow.com>
Author: DB Tsai <dbtsai@dbtsai.com>
Closes #4879 from dbtsai/breeze and squashes the following commits:
d848f65 [DB Tsai] Merge pull request #1 from mengxr/AlpineNow-breeze
c2ca6ac [Xiangrui Meng] upgrade to breeze-0.11.1
35c2f26 [Xiangrui Meng] fix LRSuite
397a208 [DB Tsai] upgrade breeze
Diffstat (limited to 'mllib/src')
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala | 4 |
1 files changed, 4 insertions, 0 deletions
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala index d2b40f2cae..aaa81da9e2 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/classification/LogisticRegressionSuite.scala @@ -372,8 +372,12 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext with M testRDD2.cache() testRDD3.cache() + val numIteration = 10 + val lrA = new LogisticRegressionWithLBFGS().setIntercept(true) + lrA.optimizer.setNumIterations(numIteration) val lrB = new LogisticRegressionWithLBFGS().setIntercept(true).setFeatureScaling(false) + lrB.optimizer.setNumIterations(numIteration) val modelA1 = lrA.run(testRDD1, initialWeights) val modelA2 = lrA.run(testRDD2, initialWeights) |