GitHub user jkbradley opened a pull request:
https://github.com/apache/spark/pull/3094
[mllib] GradientBoosting API cleanup and examples in Scala, Java
### Summary
* Made it easier to construct default Strategy and BoostingStrategy and to
set parameters using simple types.
* Added Scala and Java examples for GradientBoostedTrees
* small cleanups and fixes
### Details
GradientBoosting bug fixes (âbugâ = bad default options)
* Force boostingStrategy.weakLearnerParams.algo = Regression
* Force boostingStrategy.weakLearnerParams.impurity = impurity.Variance
* Only persist data if not yet persisted (since it causes an error if
persisted twice)
BoostingStrategy
* numEstimators: renamed to numIterations
* removed subsamplingRate (duplicated by Strategy)
* removed categoricalFeaturesInfo since it belongs with the weak learner
params (since boosting can be oblivious to feature type)
* Changed algo to var (not val) and added @BeanProperty, with overload
taking String argument
* Added assertValid() method
* Updated defaultParams() method and eliminated defaultWeakLearnerParams()
since that belongs in Strategy
Strategy (for DecisionTree)
* Changed algo to var (not val) and added @BeanProperty, with overload
taking String argument
* Added setCategoricalFeaturesInfo method taking Java Map.
* Cleaned up assertValid
* Changed valâs to defâs since parameters can now be changed.
CC: @manishamde @mengxr @codedeft
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/jkbradley/spark gbt-api
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/3094.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #3094
----
commit e9b841097e08ce3602acfb752bec0dd8edd1e43e
Author: Joseph K. Bradley <[email protected]>
Date: 2014-11-04T18:55:05Z
Summary of changes
* Made it easier to construct default Strategy and BoostingStrategy and to
set parameters using simple types.
* Added Scala and Java examples for GradientBoostedTrees
* small cleanups and fixes
Details
GradientBoosting bug fixes (âbugâ = bad default options)
* Force boostingStrategy.weakLearnerParams.algo = Regression
* Force boostingStrategy.weakLearnerParams.impurity = impurity.Variance
* Only persist data if not yet persisted (since it causes an error if
persisted twice)
BoostingStrategy
* numEstimators: renamed to numIterations
* removed subsamplingRate (duplicated by Strategy)
* removed categoricalFeaturesInfo since it belongs with the weak learner
params (since boosting can be oblivious to feature type)
* Changed algo to var (not val) and added @BeanProperty, with overload
taking String argument
* Added assertValid() method
* Updated defaultParams() method and eliminated defaultWeakLearnerParams()
since that belongs in Strategy
Strategy (for DecisionTree)
* Changed algo to var (not val) and added @BeanProperty, with overload
taking String argument
* Added setCategoricalFeaturesInfo method taking Java Map.
* Cleaned up assertValid
* Changed valâs to defâs since parameters can now be changed.
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