* Fix early stop with xgboost4j-spark
* Update XGBoost.java
* Update XGBoost.java
* Update XGBoost.java
To use -Float.MAX_VALUE as the lower bound, in case there is positive metric.
* Only update best score if the current score is better (no update when equal)
* Update xgboost-spark tutorial to fix early stopping docs.
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* wrap iterators
* enable copartition training and validationset
* add parameters
* converge code path and have init unit test
* enable multi evals for ranking
* unit test and doc
* update example
* fix early stopping
* address the offline comments
* udpate doc
* test eval metrics
* fix compilation issue
* fix example
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* documenting tracker
* Make it a separate note
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* fix scalastyle error
* temp
* add method for classifier and regressor
* update tutorial
* address the comments
* update
* Add XGBRanker to Python API doc
* Show inherited members of XGBRegressor in API doc, since XGBRegressor uses default methods from XGBModel
* Add table of contents to Python API doc
* Skip JVM doc download if not available
* Show inherited members for XGBRegressor and XGBRanker
* Expose XGBRanker to Python XGBoost module directory
* Add docstring to XGBRegressor.predict() and XGBRanker.predict()
* Fix rendering errors in Python docstrings
* Fix lint
* Adding Java/Scala doc build to Jenkins CI
* Deploy built doc to S3 bucket
* Build doc only for branches
* Build doc first, to get doc faster for branch updates
* Have ReadTheDocs download doc tarball from S3
* Update JVM doc links
* Put doc build commands in a script
* Specify Spark 2.3+ requirement for XGBoost4J-Spark
* Build GPU wheel without NCCL, to reduce binary size
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* add new
* update doc
* finish Gang Scheduling
* more
* intro
* Add sections: Prediction, Model persistence and ML pipeline.
* Add XGBoost4j-Spark MLlib pipeline example
* partial finished version
* finish the doc
* adjust code
* fix the doc
* use rst
* Convert XGBoost4J-Spark tutorial to reST
* Bring XGBoost4J up to date
* add note about using hdfs
* remove duplicate file
* fix descriptions
* update doc
* Wrap HDFS/S3 export support as a note
* update
* wrap indexing_mode example in code block
* Change doc build to reST exclusively
* Rewrite Intro doc in reST; create toctree
* Update parameter and contribute
* Convert tutorials to reST
* Convert Python tutorials to reST
* Convert CLI and Julia docs to reST
* Enable markdown for R vignettes
* Done migrating to reST
* Add guzzle_sphinx_theme to requirements
* Add breathe to requirements
* Fix search bar
* Add link to user forum
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* maven central release
* Fix typos and messages in docs
* parameter.md: Add docs for updater_seq
Mention the updater_seq parameter which sets the order of the tree
updaters to run and also specifies which ones to run. This can be
useful when pruning is not required or even a custom plugin is
being built along with xgboost.
* bump up to scala 2.11
* framework of data frame integration
* test consistency between RDD and DataFrame
* order preservation
* test order preservation
* example code and fix makefile
* improve type checking
* improve APIs
* user docs
* work around travis CI's limitation on log length
* adjust test structure
* integrate with Spark -1 .x
* spark 2.x integration
* remove spark 1.x implementation but provide instructions on how to downgrade
