GitLab

[python-package] Correctly recognize LGBMClassifier(num_class=2, objective="multiclass") as multiclass classification (#6524)

[python-package] Add `feature_names_in_` attribute for scikit-learn estimators (fixes #6279) (#6310)

[python-package] remove uses of deprecated NumPy random number generation APIs, require 'numpy>=1.17.0' (#6468)

[python-package] fix access to Dataset metadata in scikit-learn custom metrics and objectives (#6108)

[python-packages] [docs] add type hints and define 'array-like' for X, y, group in scikit-learn interface (#5757)

* [python-package] fix mypy errors about scikit-learn properties

* Update python-package/lightgbm/sklearn.py

[python-package] add type hints on feature_name and categorical_feature in sklearn interface (#5747)

* 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>

* [python-package] add type hints on Booster eval methods

* remove unnecessary changes

* fix hints

* [python-package] remove inner function _construct_dataset() in LGBMModel.fit()

* switch order

* [python-package] add type hints on predict() methods

* formatting

* allow custom weighing in sklearn api

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

* check feature names and order in predict with dataframe

* slice df in predict to remove the target

* scramble features

* handle int column names

* only change column order when needed

* include validate_features param in booster and sklearn estimators

* document validate_features argument

* use all_close in preds checks and check for assertion error to compare different arrays

* perform remapping and checks in cpp

* remove extra logs

* fixes

* revert cpp

* proposal

* remove extra arg

* lint

* restore _data_from_pandas arguments

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

* move data conversion to Predictor.predict

* use Vector2Ptr
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>