* Refactor CMake scripts.
* Remove CMake CUDA wrapper.
* Bump CMake version for CUDA.
* Use CMake to handle Doxygen.
* Split up CMakeList.
* Export install target.
* Use modern CMake.
* Remove build.sh
* Workaround for gpu_hist test.
* Use cmake 3.12.
* Revert machine.conf.
* Move CLI test to gpu.
* Small cleanup.
* Support using XGBoost as submodule.
* Fix windows
* Fix cpp tests on Windows
* Remove duplicated find_package.
The old NativeLibLoader had a short-circuit load path which modified
java.library.path and attempted to load the xgboost library from outside
the jar first, falling back to loading the library from inside the jar.
This path is a no-op every time when using XGBoost outside of it's
source tree. Additionally it triggers an illegal reflective access
warning in the module system in 9, 10, and 11.
On Java 12 the ClassLoader fields are not accessible via reflection
(separately from the illegal reflective acces warning), and so it fails
in a way that isn't caught by the code which falls back to loading the
library from inside the jar.
This commit removes that code path and always loads the xgboost library
from inside the jar file as it's a valid technique across multiple JVM
implementations and works with all versions of Java.
* Make train in xgboost4j respect print params
Previously no setting in params argument of Booster::train would prevent
the Rabit.trackerPrint call. This can fill up a lot of screen space in
the case that many folds are being trained.
* Setting "silent" in this map to "true", "True", a non-zero integer, or
a string that can be parsed to such an int will prevent printing.
* Setting "verbose_eval" to "False" or "false" will prevent printing.
* Setting "verbose_eval" to an int (or a String parseable to an int) n
will result in printing every n steps, or no printing is n is zero.
This is to match the python behaviour described here:
https://www.kaggle.com/c/rossmann-store-sales/discussion/17499
* Fixed 'slient' typo in xgboost4j test
* private access on two methods
* 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.
* Updates to Booster to support other feature importances
* Add returns for Java methods
* Pass Scala style checks
* Pass Java style checks
* Fix indents
* Use class instead of enum
* Return map string double
* A no longer broken build, thanks to mvn package local build
* Add a unit test to increase code coverage back
* Address code review on main code
* Add more unit tests for different feature importance scores
* Address more CR
* 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
* update version
* 0.82
* fix early stopping condition
* remove unused
* update comments
* udpate comments
* update test
* 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
* update version
* 0.82
* 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
* remove unused code
* refactor
* fix typo
* 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
A privilege escalation vulnerability (CVE-2017-15288) has been
identified in the Scala compilation daemon. See
https://nvd.nist.gov/vuln/detail/CVE-2017-15288
Fix: Upgrade Scala to 2.11.12.
* 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
* sparjJobThread
* update
* fix issue when spark job execution thread cannot return before we execute first()
* add back train method but mark as deprecated
* fix scalastyle error
* 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
* instrumentation
* use log console
* better measurement
* fix erros in example
* update histmaker
