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| author | Holden Karau <holden@pigscanfly.ca> | 2015-06-22 22:40:19 -0700 |
|---|---|---|
| committer | Joseph K. Bradley <joseph@databricks.com> | 2015-06-22 22:40:19 -0700 |
| commit | 164fe2aa44993da6c77af6de5efdae47a8b3958c (patch) | |
| tree | 938944e023b53542ee306edcecec99a24d66429f /mllib | |
| parent | 44fa7df64daa55bd6eb1f2c219a9701b34e1c2a3 (diff) | |
| download | spark-164fe2aa44993da6c77af6de5efdae47a8b3958c.tar.gz spark-164fe2aa44993da6c77af6de5efdae47a8b3958c.tar.bz2 spark-164fe2aa44993da6c77af6de5efdae47a8b3958c.zip | |
[SPARK-7781] [MLLIB] gradient boosted trees.train regressor missing max bins
Author: Holden Karau <holden@pigscanfly.ca>
Closes #6331 from holdenk/SPARK-7781-GradientBoostedTrees.trainRegressor-missing-max-bins and squashes the following commits:
2894695 [Holden Karau] remove extra blank line
2573e8d [Holden Karau] Update the scala side of the pythonmllibapi and make the test a bit nicer too
3a09170 [Holden Karau] add maxBins to to the train method as well
af7f274 [Holden Karau] Add maxBins to GradientBoostedTrees.trainRegressor and correctly mention the default of 32 in other places where it mentioned 100
Diffstat (limited to 'mllib')
| -rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala | 4 |
1 files changed, 3 insertions, 1 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala index 634d56d08d..f9a271f47e 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala @@ -696,12 +696,14 @@ private[python] class PythonMLLibAPI extends Serializable { lossStr: String, numIterations: Int, learningRate: Double, - maxDepth: Int): GradientBoostedTreesModel = { + maxDepth: Int, + maxBins: Int): GradientBoostedTreesModel = { val boostingStrategy = BoostingStrategy.defaultParams(algoStr) boostingStrategy.setLoss(Losses.fromString(lossStr)) boostingStrategy.setNumIterations(numIterations) boostingStrategy.setLearningRate(learningRate) boostingStrategy.treeStrategy.setMaxDepth(maxDepth) + boostingStrategy.treeStrategy.setMaxBins(maxBins) boostingStrategy.treeStrategy.categoricalFeaturesInfo = categoricalFeaturesInfo.asScala.toMap val cached = data.rdd.persist(StorageLevel.MEMORY_AND_DISK) |