- 15 Feb, 2023 1 commit
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James Lamb authored
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- 31 Jan, 2023 1 commit
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IdoKendo authored
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- 19 Jan, 2023 1 commit
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IdoKendo authored
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- 13 Jan, 2023 1 commit
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IdoKendo authored
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- 12 Jan, 2023 1 commit
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James Lamb authored
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- 28 Dec, 2022 1 commit
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Yifei Liu authored
* 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:
Nikita Titov <nekit94-08@mail.ru> * Update src/boosting/bagging.hpp 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:
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- 04 Nov, 2022 1 commit
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James Lamb authored
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- 07 Oct, 2022 1 commit
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James Lamb authored
[ci] prefer CPython in Windows test environment and use safer approach for cleaning up network (fixes #5509) (#5510)
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- 12 Sep, 2022 1 commit
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James Lamb authored
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- 19 Jun, 2022 1 commit
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david-cortes authored
[python-package] Use scikit-learn interpretation of negative `n_jobs` and change default to number of cores (#5105) * use joblib formula for negative n_jobs * correction for n_jobs calculation * use more robust cpu_count from joblib * change default n_jobs to number of cores * fix detection of num_threads under parameters * better handling of n_jobs at prediction time * fix incorrect usage of list.pop * correct pop/remove yet again * Update python-package/lightgbm/sklearn.py Co-authored-by:
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- 23 Feb, 2022 1 commit
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Miguel Trejo Marrufo authored
* docs: weight parameter non-negative * docs: weights non negative only for train data * docs: weights should be non negative for validation data * typo in html render * docs: brief weights non-negative description
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- 17 Jan, 2022 1 commit
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James Lamb authored
* add test for custom objective with regressor * add test for custom binary classification objective with classifier * isort * got tests working for multiclass * update docs * train deeper model for classifier * Apply suggestions from code review Co-authored-by:
José Morales <jmoralz92@gmail.com> * Apply suggestions from code review Co-authored-by:
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- 10 Dec, 2021 1 commit
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Nikita Titov authored
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- 06 Dec, 2021 2 commits
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James Lamb authored
* [python-package][dask] handle failures parsing work host names * add tests * revert local testing changes
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James Lamb authored
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- 02 Dec, 2021 1 commit
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James Lamb authored
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- 01 Dec, 2021 1 commit
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James Lamb authored
* [python-package] fix mypy error about missing type hint in dask.py * list of lists * use different variable * use append()
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- 30 Nov, 2021 1 commit
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Nikita Titov authored
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- 20 Nov, 2021 1 commit
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Nikita Titov authored
* Update test_plotting.py * Update dask.py * Update sklearn.py * Update test_sklearn.py * Update basic.py * Update engine.py * Update test_engine.py * Update basic.py * Update basic.py * Update engine.py
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- 15 Nov, 2021 1 commit
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James Lamb authored
* [python] add type hints for custom objective and metric functions in scikit-learn interface * update type hints * remote unnecessary input * Update python-package/lightgbm/sklearn.py Co-authored-by:
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- 08 Nov, 2021 1 commit
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James Lamb authored
* [docs] [dask] Add return information to Dask fit() docs (fixes #4402) * put return before note
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- 20 Sep, 2021 1 commit
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Nikita Titov authored
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- 17 Sep, 2021 1 commit
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José Morales authored
[python-package] Support 2d collections as input for `init_score` in multiclass classification task (#4150) * initial implementation of init_score for multiclass classification * check for 1d or 2d collection in init_score * remove dataset import * initial comments * update dask test and docstrings * update docstrings * move logic to set_field. reshape back on get_field * add type hints and update docstrings for dask. fix Dataset.set_field * revert wrong docstrings and type hints * add extra comma for consistency * prefix private functions with underscore add type hints to new functions make commas consistent in dask and basic * add missing spaces after type hint * remove shape condition for dataframe in is_2d_collection Co-authored-by:Nikita Titov <nekit94-12@hotmail.com>
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- 04 Sep, 2021 1 commit
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Nikita Titov authored
* deprecate `silent` and standalone `verbose` args. Prefer global `verbose` param * simplify code * Rephrase warning messages
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- 30 Aug, 2021 1 commit
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Nikita Titov authored
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- 29 Aug, 2021 1 commit
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Nikita Titov authored
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- 28 Aug, 2021 1 commit
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Nikita Titov authored
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- 27 Aug, 2021 1 commit
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Nikita Titov authored
* Reffer to string type as `str` and and commas in `list of ...` types * update `libpath.py` too
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- 03 Aug, 2021 1 commit
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José Morales authored
* find all needed ports in each worker at once * lint * better naming * use _HostWorkers in test
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- 08 Jul, 2021 1 commit
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José Morales authored
* call predict on one row of data to determine output shape * make DaskLGBMRanker predict method equal to the others * remove extra drop_axis
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- 07 Jul, 2021 1 commit
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James Lamb authored
[dask] Make output of feature contribution predictions for sparse matrices match those from sklearn estimators (fixes #3881) (#4378) * test_classifier working * adding tests * docs * tests * revert unnecessary changes in tests * test output type * linting * linting * use from_delayed() instead * docstring pycodestyle is happy with * isort * put pytest skips back * respect sparse return type * fix doc * remove unnecessary dask_array_concatenate() * Apply suggestions from code review Co-authored-by:
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- 05 Jul, 2021 1 commit
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Nikita Titov authored
* Update test_sklearn.py * Update test_basic.py * Update dask.py * Update basic.py * Update basic.py * Update basic.py * Update basic.py * Update callback.py
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- 28 Jun, 2021 2 commits
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James Lamb authored
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Frank Fineis authored
* es WiP, need to add eval_sample_weight and eval_group * add weight, group to dask es. WiP. * dask es reorg * Update python-package/lightgbm/dask.py _train_part model.fit args to lines Co-authored-by:
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- 26 Jun, 2021 1 commit
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James Lamb authored
* [dask] pass predict() kwargs through when input is a Dask Array * add tests * Apply suggestions from code review Co-authored-by:
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- 15 Jun, 2021 1 commit
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Frank Fineis authored
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- 15 May, 2021 1 commit
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NovusEdge authored
* added f-string to dask.py * Update python-package/lightgbm/dask.py Co-authored-by:
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- 04 May, 2021 1 commit
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Andrew Ziem authored
* Correct spelling Most changes were in comments, and there were a few changes to literals for log output. There were no changes to variable names, function names, IDs, or functionality. * Clarify a phrase in a comment Co-authored-by:
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- 21 Apr, 2021 1 commit
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Frank Fineis authored
* fix typo in dask _train as mentioned in 4101 * Update python-package/lightgbm/dask.py Co-authored-by:
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- 01 Apr, 2021 1 commit
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jmoralez authored
* include voting_parallel tree_learner in test_regressor, test_classifier and test_ranker * remove test for warnings and test for error when using feature_parallel * use real names for tree_learner intest and include test for aliases. use the error message in the test for error in feature parallel * split all tests with rf in test_classifier * remove task parametrization for tree_learner aliases test. smaller input data from feature_parallel error * define task for tree_learner aliases
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