GitLab

* Move all examples to dontrun

* update docs

* fix nested dontrun

* remove :: in examples

* run_dontrun in pkgdown
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [doc] better doc for `keep_training_booster`

* Update python-package/lightgbm/engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* fix bug for GOSS with customized objective (fixes #3243)

* Apply suggestions from code review
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update multiclass_objective.hpp

* Apply suggestions from code review

* Update src/objective/multiclass_objective.hpp

* Apply suggestions from code review

* Update test_basic.R

* Update test_basic.R

* Update src/objective/multiclass_objective.hpp
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Fix bug introduced in PR #2992 for Fast predict

* Faster Fast predict API

* Add const to SingleRow Fast methods

* [python] add return_cvbooster flag to cv function and rename _CVBooster to make public (#283,#2105)

* [python] Reduce expected metric of unit testing

* [docs] add the CVBooster to the documentation

* [python] reflect the review comments

- Add some clarifications to the documentation
- Rename CVBooster.append to make private
- Decrease iteration rounds of testing to save CI time
- Use CVBooster as root member of lgb

* [python] add more checks in testing for cv
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [python] add docstring for instance attributes of CVBooster
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [python] fix docstring
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [R-package] fix early_stopping_round <= 0

* linting

* [R-package] deprecate lgb.prepare() and lgb.prepare2()

* linting

* renaming

* updated docs

* linting

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* one more comment fix

* remove comment about int being dangerous

* empty commit
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [python][scikit-learn] New unit tests and maintenance

* Includes multioutput tests
* Includes RandomizedSearchCV test
* Updates dataset parameters to eliminate FutureWarning

* Change to n_class in load_digits

* Fix spacing

* Changes after review

* Also updates validation split in grid and random search

* Include skipif for classes_ attr

* Updates checks for classes and order
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update .vsts-ci.yml

* Update .travis.yml

Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* ~ Modified name of method DatasetLoader::CostructFromSampleData to DatasetLoader::ConstructFromSampleData.
& Build passes for Debug, Debug_DLL, DLL and Release (not tested Debug_mpi and Release_mpi).

* ~ Refactored indentations.
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [R-package] make package installable with CRAN toolchain (fixes #2960)

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* remove GPU stuff

* use wildcard to find objects to build

* use -lomp

* build configure before moving files

* using wildcard for objects

* Update .github/workflows/main.yml
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add explicit objects back

* reduce allowed R CMD check NOTEs and catch stderr from build-cran-package on Windows

* fixing things

* pin autoconf version

* show diff

* add automake back

* run less checks

* command was in the wrong place

* fix autoconf version

* change strategy for handling configure

* fix Rbuildignore

* fix NOTEs

* fix notes about unrecognized files

* fixing extra files

* remove USE_R35

* add OpenMP check for Mac CRAN build

* run all checks

* Apply suggestions from code review
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* suggestions from code review

* undo indenting

* remove 03 from Makevars.win.in

* update language about OpenMP in configure script

* checking if configure.ac check works

* add autoconf back

* remove testing code in configure.ac

* more fixes for CI on configure script

* print git diff

* add VERSION.txt when checking configure

* fix relative paths

* remove git diff
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* fix

* Apply suggestions from code review

* [R-package] Add tests on lgb.check.eval, lgb.unloader, and lgb.encode.char

* remove accidental test file

* regenerated docs

* [ci] remove unnecessary R_CHECK_FORCE_SUGGESTS in CI scripts

* remove unused test data

* [R-package] add test on importance types

* linting

* more changes

* factor out ggplot2

* update CI

* remove library()

* linting

* reduce NOTEs on Windows

Co-authored-by: Ubuntu <shiyu@gbdt-shiyu.ren3kv4wanvufliwrpy4k03lsf.xx.internal.cloudapp.net>

* Add capability to get possible max and min values for a model

* Change implementation to have return value in tree.cpp, change naming to upper and lower bound, move implementation to gdbt.cpp

* Update include/LightGBM/c_api.h
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Change iteration to avoid potential overflow, add bindings to R and Python and a basic test

* Adjust test values

* Consider const correctness and multithreading protection

* Put everything possible as const

* Include shared_mutex, for now as unique_lock

* Update test values

* Put everything possible as const

* Include shared_mutex, for now as unique_lock

* Make PredictSingleRow const and share the lock with other reading threads

* Update test values

* Add test to check that model is exactly the same in all platforms

* Try to parse the model to get the expected values

* Try to parse the model to get the expected values

* Fix implementation, num_leaves can be lower than the leaf_value_ size

* Do not check for num_leaves to be smaller than actual size and get back to test with hardcoded value

* Change test order

* Add gpu_use_dp option in test

* Remove helper test method

* Remove TODO

* Add preprocessing option to compile with c++17

* Update python-package/setup.py
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Remove unwanted changes

* Move option

* Fix problems introduced by conflict fix

* Avoid switching to c++17 and use yamc mutex library to access shared lock functionality

* Add extra yamc include

* Change header order

* some lint fix

* change include order and remove some extra blank lines

* Further fix lint issues

* Update c_api.cpp

* Further fix lint issues

* Move yamc include files to a new yamc folder

* Use standard unique_lock

* Update windows/LightGBM.vcxproj
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update windows/LightGBM.vcxproj.filters
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Fix problems coming from merge conflict resolution
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: joanfontanals <jfontanals@ntent.com>
Co-authored-by: Guolin Ke <guolin.ke@outlook.com>

In the current implementation, the index is an int32, which will segfault with large data sets and a large number of estimators.

* [performance] Add Fast methods to C API for SingleRow Predictions

 * Add methods to C API to make single-row predictions faster:

   - LGBM_BoosterPredictForMatSingleRowFastInit (setup)
   - LGBM_BoosterPredictForMatSingleRowFast (predict)
   - LGBM_FastConfigFree (cleanup setup outputs)

* Code syle cleanup

* Fix lint errors

* [performance] Revert FastConfig improvement to pass data at init

This reduces optimization by 5% / 30% with this branch but makes it so it can be used for higher level wrappers in MMLSpark.
And outside it as well.

* [performance] Introduce Fast variants for SingleRow predictors.

Although this already provides performance gains by itself for any
callers, two new functions were added to Java's SWIG interfaces to
exploit that AND the GetPrimitiveArrayCritical data fetches.

* [tests/profiling] Profile Fast predict methods

Build with -DBUILD_PROFILING_TESTS=ON and copy the default
model trained on the Higgs dataset from the benchmarks repo

 https://github.com/guolinke/boosting_tree_benchmarks.git



to LightGBM repo root and run the lightgbm_profile_* binaries.

The single instance used is the first row from that dataset.

* Update comment on CMakeLists.

* Fix doxygen-introduced issue (#threads)

* Fix conflicts due to new RowFunctionFromCSR signature in master

* Change FastConfig ncol to int32_t.

* Removed profiling folder

* fix doxygen typo include/LightGBM/c_api.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* fix doxygen typo include/LightGBM/c_api.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* fix doxygen typo include/LightGBM/c_api.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Doxygen: change new docstrings to double back-quote
Co-authored-by: alberto.ferreira <alberto.ferreira@feedzai.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* feature importance type in saved model file

* fix nullptr

* fixed formatting

* fix python/R

* Update src/c_api.cpp

* Apply suggestions from code review
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* fix c_api test

* fix swig

* minor docs improvements and added defines for importance types
Co-authored-by: StrikerRUS <nekit94-12@hotmail.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

[python][scikit-learn] Fixes a bug that prevented using multiple eval_metrics in LGBMClassifier (#3222)

* Fixes a bug that prevented using multiple eval_metrics in LGBMClassifier

* Move bug-fix test to the test_metrics unit-test

* Fix test to avoid issues with existing tests

* Fix coding-style error
Co-authored-by: German I Ramirez-Espinoza <gire@home>