* add interaction constraints
* enable both interaction and monotonic constraints at the same time
* fix lint
* add R test, fix lint, update demo
* Use dmlc::JSONReader to express interaction constraints as nested lists; Use sparse arrays for bookkeeping
* Add Python test for interaction constraints
* make R interaction constraints parameter based on feature index instead of column names, fix R coding style
* Fix lint
* Add BlueTea88 to CONTRIBUTORS.md
* Short circuit when no constraint is specified; address review comments
* Add tutorial for feature interaction constraints
* allow interaction constraints to be passed as string, remove redundant column_names argument
* Fix typo
* Address review comments
* Add comments to Python test
- previously, vec_ in DeviceShard wasn't updated on copy; as a result,
the shards continued to refer to the old HostDeviceVectorImpl object,
which resulted in a dangling pointer once that object was deallocated
* Fix#3648: XGBClassifier.predict() should return margin scores when output_margin=True
* Fix tests to reflect correct implementation of XGBClassifier.predict(output_margin=True)
* Fix flaky test test_with_sklearn.test_sklearn_api_gblinear
* Replaced std::vector with HostDeviceVector in MetaInfo and SparsePage.
- added distributions to HostDeviceVector
- using HostDeviceVector for labels, weights and base margings in MetaInfo
- using HostDeviceVector for offset and data in SparsePage
- other necessary refactoring
* Added const version of HostDeviceVector API calls.
- const versions added to calls that can trigger data transfers, e.g. DevicePointer()
- updated the code that uses HostDeviceVector
- objective functions now accept const HostDeviceVector<bst_float>& for predictions
* Updated src/linear/updater_gpu_coordinate.cu.
* Added read-only state for HostDeviceVector sync.
- this means no copies are performed if both host and devices access
the HostDeviceVector read-only
* Fixed linter and test errors.
- updated the lz4 plugin
- added ConstDeviceSpan to HostDeviceVector
- using device % dh::NVisibleDevices() for the physical device number,
e.g. in calls to cudaSetDevice()
* Fixed explicit template instantiation errors for HostDeviceVector.
- replaced HostDeviceVector<unsigned int> with HostDeviceVector<int>
* Fixed HostDeviceVector tests that require multiple GPUs.
- added a mock set device handler; when set, it is called instead of cudaSetDevice()
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* interrupted exception is not rethrown
* 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
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* fix update checkpoint func
* added xgbranker
* fixed predict method and ranking test
* reformatted code in accordance with pep8
* fixed lint error
* fixed docstring and added checks on objective
* added ranking demo for python
* fixed suffix in rank.py
* Add basic Span class based on ISO++20.
* Use Span<Entry const> instead of Inst in SparsePage.
* Add DeviceSpan in HostDeviceVector, use it in regression obj.
This pull request amends the broken #3062 allow Spark 2.2 to work.
Please note this won't work in Spark <=2.1 as sc.removeSparkListener was implemented in Spark 2.2. (So perhaps a more general method is better, although that is what was attempted in #3062)
This PR fixes: #3208, #3151 and the discussion in #1927.
I do find it strange that #3062 dose not work in Spark 2.2, it's probably due to some sort of public/private issue in the org.apache.spark.scheduler.LiveListenerBus class inheritance (In Spark itself). The error is: `java.lang.NoSuchMethodError: org.apache.spark.scheduler.LiveListenerBus.removeListener(Ljava/lang/Object;)V`
* 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
* Revert "Fix #3485, #3540: Don't use dropout for predicting test sets (#3556)"
This reverts commit 44811f233071c5805d70c287abd22b155b732727.
* Document behavior of predict() for DART booster
* Add notice to parameter.rst
* add back train method but mark as deprecated
* add back train method but mark as deprecated
* fix scalastyle error
* fix scalastyle error
* partial finish
* no test
* add test cases
* add test cases
* address comments
* add test for regressor
* fix typo
