GitLab

* [ci] [c++] use 'pre-commit' to run 'cpplint', upgrade to 'cpplint' 2.0.2

* remove bashisms

* one more pipefail use

* another pipefail

Co-authored-by: Atanas Dimitrov <nasko119@abv.bg>
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* add parameter data_sample_strategy

* abstract GOSS as a sample strategy(GOSS1), togetherwith origial GOSS (Normal Bagging has not been abstracted, so do NOT use it now)

* abstract Bagging as a subclass (BAGGING), but original Bagging members in GBDT are still kept

* fix some variables

* remove GOSS(as boost) and Bagging logic in GBDT

* rename GOSS1 to GOSS(as sample strategy)

* add warning about use GOSS as boosting_type

* a little ; bug

* remove CHECK when "gradients != nullptr"

* rename DataSampleStrategy to avoid confusion

* remove and add some ccomments, followingconvention

* fix bug about GBDT::ResetConfig (ObjectiveFunction inconsistencty bet…

* add std::ignore to avoid compiler warnings (anpotential fails)

* update Makevars and vcxproj

* handle constant hessian

move resize of gradient vectors out of sample strategy

* mark override for IsHessianChange

* fix lint errors

* rerun parameter_generator.py

* update config_auto.cpp

* delete redundant blank line

* update num_data_ when train_data_ is updated

set gradients and hessians when GOSS

* check bagging_freq is not zero

* reset config_ value

merge ResetBaggingConfig and ResetGOSS

* remove useless check

* add ttests in test_engine.py

* remove whitespace in blank line

* remove arguments verbose_eval and evals_result

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

reduce num_boost_round
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update src/boosting/sample_strategy.cpp

modify warning about setting goss as `boosting_type`
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_engine.py

replace load_boston() with make_regression()

remove value checks of mean_squared_error in test_sample_strategy_with_boosting()

* Update tests/python_package_test/test_engine.py

add value checks of mean_squared_error in test_sample_strategy_with_boosting()

* Modify warnning about using goss as boosting type

* Update tests/python_package_test/test_engine.py

add random_state=42 for make_regression()

reduce the threshold of mean_square_error

* Update src/boosting/sample_strategy.cpp
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* remove goss from boosting types in documentation

* Update src/boosting/bagging.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/bagging.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/goss.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update src/boosting/goss.hpp
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* rename GOSS with GOSSStrategy

* update doc

* address comments

* fix table in doc

* Update include/LightGBM/config.h
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* update documentation

* update test case

* revert useless change in test_engine.py

* add tests for evaluation results in test_sample_strategy_with_boosting

* include <string>

* change to assert_allclose in test_goss_boosting_and_strategy_equivalent

* more tolerance in result checking, due to minor difference in results of gpu versions

* change == to np.testing.assert_allclose

* fix test case

* set gpu_use_dp to true

* change --report to --report-level for rstcheck

* use gpu_use_dp=true in test_goss_boosting_and_strategy_equivalent

* revert unexpected changes of non-ascii characters

* revert unexpected changes of non-ascii characters

* remove useless changes

* allocate gradients_pointer_ and hessians_pointer when necessary

* add spaces

* remove redundant virtual

* include <LightGBM/utils/log.h> for USE_CUDA

* check for  in test_goss_boosting_and_strategy_equivalent

* check for identity in test_sample_strategy_with_boosting

* remove cuda  option in test_sample_strategy_with_boosting

* Update tests/python_package_test/test_engine.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update tests/python_package_test/test_engine.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* ResetGradientBuffers after ResetSampleConfig

* ResetGradientBuffers after ResetSampleConfig

* ResetGradientBuffers after bagging

* remove useless code

* check objective_function_ instead of gradients

* enable rf with goss

simplify params in test cases

* remove useless changes

* allow rf with feature subsampling alone

* change position of ResetGradientBuffers

* check for dask

* add parameter types for data_sample_strategy
Co-authored-by: Guangda Liu <v-guangdaliu@microsoft.com>
Co-authored-by: Yu Shi <shiyu_k1994@qq.com>
Co-authored-by: GuangdaLiu <90019144+GuangdaLiu@users.noreply.github.com>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* add huber regression for cuda_exp

* renew tree output on GPU

add test cases for regression objectives

* remove useless changes

* add white space

* fix test_regression

* fix cuda_exp ci

* fix ci failures introduced by #5279

* cleanup cuda.yml

* fix test.sh

* clean up test.sh

* clean up test.sh

* skip lines by cuda_exp in test_register_logger

* Update tests/python_package_test/test_utilities.py
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Add Eigen library.

* Working for simple test.

* Apply changes to config params.

* Handle nan data.

* Update docs.

* Add test.

* Only load raw data if boosting=gbdt_linear

* Remove unneeded code.

* Minor updates.

* Update to work with sk-learn interface.

* Update to work with chunked datasets.

* Throw error if we try to create a Booster with an already-constructed dataset having incompatible parameters.

* Save raw data in binary dataset file.

* Update docs and fix parameter checking.

* Fix dataset loading.

* Add test for regularization.

* Fix bugs when saving and loading tree.

* Add test for load/save linear model.

* Remove unneeded code.

* Fix case where not enough leaf data for linear model.

* Simplify code.

* Speed up code.

* Speed up code.

* Simplify code.

* Speed up code.

* Fix bugs.

* Working version.

* Store feature data column-wise (not fully working yet).

* Fix bugs.

* Speed up.

* Speed up.

* Remove unneeded code.

* Small speedup.

* Speed up.

* Minor updates.

* Remove unneeded code.

* Fix bug.

* Fix bug.

* Speed up.

* Speed up.

* Simplify code.

* Remove unneeded code.

* Fix bug, add more tests.

* Fix bug and add test.

* Only store numerical features

* Fix bug and speed up using templates.

* Speed up prediction.

* Fix bug with regularisation

* Visual studio files.

* Working version

* Only check nans if necessary

* Store coeff matrix as an array.

* Align cache lines

* Align cache lines

* Preallocation coefficient calculation matrices

* Small speedups

* Small speedup

* Reverse cache alignment changes

* Change to dynamic schedule

* Update docs.

* Refactor so that linear tree learner is not a separate class.

* Add refit capability.

* Speed up

* Small speedups.

* Speed up add prediction to score.

* Fix bug

* Fix bug and speed up.

* Speed up dataload.

* Speed up dataload

* Use vectors instead of pointers

* Fix bug

* Add OMP exception handling.

* Change return type of LGBM_BoosterGetLinear to bool

* Change return type of LGBM_BoosterGetLinear back to int, only parameter type needed to change

* Remove unused internal_parent_ property of tree

* Remove unused parameter to CreateTreeLearner

* Remove reference to LinearTreeLearner

* Minor style issues

* Remove unneeded check

* Reverse temporary testing change

* Fix Visual Studio project files

* Restore LightGBM.vcxproj.filters

* Speed up

* Speed up

* Simplify code

* Update docs

* Simplify code

* Initialise storage space for max num threads

* Move Eigen to include directory and delete unused files

* Remove old files.

* Fix so it compiles with mingw

* Fix gpu tree learner

* Change AddPredictionToScore back to const

* Fix python lint error

* Fix C++ lint errors

* Change eigen to a submodule

* Update comment

* Add the eigen folder

* Try to fix build issues with eigen

* Remove eigen files

* Add eigen as submodule

* Fix include paths

* Exclude eigen files from Python linter

* Ignore eigen folders for pydocstyle

* Fix C++ linting errors

* Fix docs

* Fix docs

* Exclude eigen directories from doxygen

* Update manifest to include eigen

* Update build_r to include eigen files

* Fix compiler warnings

* Store raw feature data as float

* Use float for calculating linear coefficients

* Remove eigen directory from GLOB

* Don't compile linear model code when building R package

* Fix doxygen issue

* Fix lint issue

* Fix lint issue

* Remove uneeded code

* Restore delected lines

* Restore delected lines

* Change return type of has_raw to bool

* Update docs

* Rename some variables and functions for readability

* Make tree_learner parameter const in AddScore

* Fix style issues

* Pass vectors as const reference when setting tree properties

* Make temporary storage of serial_tree_learner mutable so we can make the object's methods const

* Remove get_raw_size, use num_numeric_features instead

* Fix typo

* Make contains_nan_ and any_nan_ properties immutable again

* Remove data_has_nan_ property of tree

* Remove temporary test code

* Make linear_tree a dataset param

* Fix lint error

* Make LinearTreeLearner a separate class

* Fix lint errors

* Fix lint error

* Add linear_tree_learner.o

* Simulate omp_get_max_threads if openmp is not available

* Update PushOneData to also store raw data.

* Cast size to int

* Fix bug in ReshapeRaw

* Speed up code with multithreading

* Use OMP_NUM_THREADS

* Speed up with multithreading

* Update to use ArrayToString

* Fix tests

* Fix test

* Fix bug introduced in merge

* Minor updates

* Update docs

* Add interaction constraints functionality.

* Minor fixes.

* Minor fixes.

* Change lambda to function.

* Fix gpu bug, remove extra blank lines.

* Fix gpu bug.

* Fix style issues.

* Try to fix segfault on MACOS.

* Fix bug.

* Fix bug.

* Fix bugs.

* Change parameter format for R.

* Fix R style issues.

* Change string formatting code.

* Change docs to say R package not supported.

* Remove R functionality, moving to separate PR.

* Keep track of branch features in tree object.

* Only track branch features when feature interactions are enabled.

* Fix lint error.

* Update docs and simplify tests.

This reverts commit 656d2676.

* speed up for const hessian

* rename template

* some refactorings

* refine

* refine

* simplify codes

* fix random in feature histogram

* code refine

* refine

* try fix

* make gcc happy

* remove timer

* rollback some changes

* more templates

* fix a bug

* reduce the cost of timer

* fix gpu

* fix bug

* fix gpu

* fixed cpplint errors

* fixed more cpplint errors

* speed up multi-val bin subset for bagging

* remove the duplicated codes

* code refine

* some codes refactoring

* move `is_constant_hessian` into `TrainingShareStates`

* refine

* fix bug

* fix bug when num_groups_ < 0

* fix gpu

* fix gpu bagging

* fix gpu bug

* typo

* Update src/treelearner/serial_tree_learner.h

* fix a bug when bagging with reset_config

* clean code

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* fix RF's bugs

* fix tests

* rollback num_iterations

* fix a bug and reduce memory costs

* reduce memory cost

Init has been updated to allow for feature_fraction == 1.0f but the change has not been copyed in the ResetConfig function.

* fix RF's bug withMAPE

* simplify rf's code & support multi-class rf

* fix bug & add test

* add more tests

* Update test_engine.py

* Update test_engine.py

* [WIP] refine config

* [wip] ready for the auto code generate

* auto generate config codes

* use with to open file

* fix bug

* fix pylint

* fix bug

* fix pylint

* fix bugs.

* tmp for failed test.

* fix tests.

* added nthreads alias

* added new aliases from new config.h

* fixed duplicated alias

* refactored parameter_generator.py

* added new aliases from config.h and removed remaining old names

* fix bugs & some miss alias

* added aliases

* add more descriptions.

* add comment.

* finish the data loading part

* allow prediction.

* fix bug for decision type.

* finish split finding part

* fix bugs.

* bug fixed. add a test .

* fix pep8 .

* update documents.

* fix test bugs.

* fix a format

* fix import error in python test.

* disable missing handle in categorial features.

* fix a bug.

* add more tests.

* fix pep8

* fix bugs.

* remove the missing handle code for categorical feature.

* add draft of RF.

* fix score bugs.

* fix scores.

* fix tests.

* update document

* fix GetPredictAt