- Implement a columnar adapter.
- Refactor Python pandas handling code to avoid converting into a single numpy array.
- Add support in R for transforming columns.
- Support R data.frame and factor type.
- Use the `linalg::Matrix` for storing gradients.
- New API for the custom objective.
- Custom objective for multi-class/multi-target is now required to return the correct shape.
- Custom objective for Python can accept arrays with any strides. (row-major, column-major)
* Use array interface for CSC matrix.
Use array interface for CSC matrix and align the interface with CSR and dense.
- Fix nthread issue in the R package DMatrix.
- Unify the behavior of handling `missing` with other inputs.
- Unify the behavior of handling `missing` around R, Python, Java, and Scala DMatrix.
- Expose `num_non_missing` to the JVM interface.
- Deprecate old CSR and CSC constructors.
* [R] Use new interface for creating DMatrix from CSR.
- CSC is still using the old API.
The old API is not aware of `nthread` parameter, which makes DMatrix to use all available
thread during construction and during transformation lie `SparsePage` -> `CSCPage`.
This is the one last PR for removing omp global variable.
* Add context object to the `DMatrix`. This bridges `DMatrix` with https://github.com/dmlc/xgboost/issues/7308 .
* Require context to be available at the construction time of booster.
* Add `n_threads` support for R csc DMatrix constructor.
* Remove `omp_get_max_threads` in R glue code.
* Remove threading utilities that rely on omp global variable.
* Add feature score support for linear model.
* Port R interface to the new implementation.
* Add linear model support in Python.
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
* Add management functions for global configuration: XGBSetGlobalConfig(), XGBGetGlobalConfig().
* Add Python interface: set_config(), get_config(), and config_context().
* Add unit tests for Python
* Add R interface: xgb.set.config(), xgb.get.config()
* Add unit tests for R
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
* [R] Add a compatibility layer to load Booster from an old RDS
* Modify QuantileHistMaker::LoadConfig() to be backward compatible with 1.1.x
* Add a big warning about compatibility in QuantileHistMaker::LoadConfig()
* Add testing suite
* Discourage use of saveRDS() in CRAN doc
* Add bindings for serialization.
* Change `xgb.save.raw' into full serialization instead of simple model.
* Add `xgb.load.raw' for unserialization.
* Run devtools.
* Simplify DropTrees calling logic
* Add `training` parameter for prediction method.
* [Breaking]: Add `training` to C API.
* Change for R and Python custom objective.
* Correct comment.
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
* adding support for matrix slicing with query ID for cross-validation
* hail mary test of unrar installation for windows tests
* trying to modify tests to run in Github CI
* Remove dependency on wget and unrar
* Save error log from R test
* Relax assertion in test_training
* Use int instead of bool in C function interface
* Revise R interface
* Add XGDMatrixSliceDMatrixEx and keep old XGDMatrixSliceDMatrix for API compatibility
* [R] MSVC compatibility
* [GPU] allow seed in BernoulliRng up to size_t and scale to uint32_t
* R package build with cmake and CUDA
* R package CUDA build fixes and cleanups
* always export the R package native initialization routine on windows
* update the install instructions doc
* fix lint
* use static_cast directly to set BernoulliRng seed
* [R] demo for GPU accelerated algorithm
* tidy up the R package cmake stuff
* R pack cmake: installs main dependency packages if needed
* [R] version bump in DESCRIPTION
* update NEWS
* added short missing/sparse values explanations to FAQ
* [R] make sure things work for a single split model; fixes#2191
* [R] add option use_int_id to xgb.model.dt.tree
* [R] add example of exporting tree plot to a file
* [R] set save_period = NULL as default in xgboost() to be the same as in xgb.train; fixes#2182
* [R] it's a good practice after CRAN releases to bump up package version in dev
* [R] allow xgb.DMatrix construction from integer dense matrices
* [R] xgb.DMatrix: silent parameter; improve documentation
* [R] xgb.model.dt.tree code style changes
* [R] update NEWS with parameter changes
* [R] code safety & style; handle non-strict matrix and inherited classes of input and model; fixes#2242
* [R] change to x.y.z.p R-package versioning scheme and set version to 0.6.4.3
* [R] add an R package versioning section to the contributors guide
* [R] R-package/README.md: clean up the redundant old installation instructions, link the contributors guide
* [R-package] JSON tree dump interface
* [R-package] precision bugfix in xgb.attributes
* [R-package] bugfix for cb.early.stop called from xgb.cv
* [R-package] a bit more clarity on labels checking in xgb.cv
* [R-package] test JSON dump for gblinear as well
* whitespace lint
