GitLab

* 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: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_dask.py

_train_part model.fit args to lines, pt2
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py

_train_part model.fit args to lines pt3
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update tests/python_package_test/test_dask.py

dask_model.fit args to lines
Co-authored-by: James Lamb <jaylamb20@gmail.com>

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

* Update python-package/lightgbm/dask.py

use is instead of id()
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

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

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

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update python-package/lightgbm/dask.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* applying changes to eval_set PR WiP

* dask support for eval_names, eval_metric, eval_stopping_rounds

* add evals_result checks and other eval_set attribute-related test checks. need to merge master - WiP

* fix lint errors in test_dask.py

* drop group_shape from _lgbmmodel_doc_fit.format for non-rankers, add support for eval_at for dask ranker

* add eval_at to test_dask eval_set ranker tests

* add back group_shape to lgbmmmodel docs, tighten tests

* drop random eval weights from early stopping, probably causing training to terminate too early

* add eval data templates to sklearn fit docs, add eval data docs to dask

* add n_features to _create_data, eval_set tests stop w/ desirable tree counts

* import alphabetically

* add back get_worker for eval_set error handling

* test_dask argmin typo

* push forgotten eval_names bugfix

* eval_stopping_rounds -> early_stopping_rounds, fix failing non-es test

* change default eval_at to tuple 1-5

* re-drop get_worker

* drop early stopping support from eval_set commits, move eval_set worker check prior to client.submit

* add eval_class_weight and eval_init_score to lightgbm/dask, WiP

* clean up eval_set tests, allow user to specify fewer eval_names, clswghts than eval_sets

* remove redundant backslash

* lint fixes

* fix eval_at, eval_metric duplication, let eval_at be Iterable not just Tuple

* use all data_outputs for test_eval_set tests

* undo newlines from first pr

* add custom_eval_metric test, correct issue with eval_at and metric names

* move _constant_metric outside of test

* dataset reference names instead of __strings__

* add padding to eval_set parts makes each part has same len(eval_set)

* eval set code clean up

* revert n_evals to be max len eval_set across all parts on worker

* pylint errors in _DatasetNames

* more pylint fixes

* pylinting...

* add by pytest.mark, mistakenly deleted during merge conflict resolution

* address code review comments

* add _pad_eval_names to handle nondeterministic evals_result_ valid set names

* change not evaluated evals_result_ test criteria

* address fit eval docs issues, switch _DatasetNames to Enum

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

* update eval_metrics, eval_at dask fit docstr to match sklearn, make tests reflect that l2 (rmse), logloss in evals_result_ by default

* address eval_set dict keys naming in docstr and training eval_set naming issue

* in test_dask check for obj-default metric names in eval_results, remove check for training key

* lint fixes for _pad_eval_names

* remove unnecessary breaklinen in _pad_eval_names docstr

* use Enum.member syntax not Enum.member.name

* remove str from supported eval_at types

* add whitespace and remove DaskDataframes mention from eval_ param docstrs in _train

* remove "of shape = [n_samples]" from group_shape docs

* add eval_at base_doc in DaskLGBMRanker.fit

* remove excess paren from eval_names docs in _train

* make requested changes to test_dask.py

* remove Optional() wrapper on eval_at

* add _lgbmmodel_doc_custom_eval_note to dask.py fit.__doc__

* fix ordering of .sklearn imports to attempt lint fix

* dask custom eval note to f-string pt1
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* dask custom eval note to f-string pt 2
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* dask custom eval note to f-string pt 3
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* 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: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Clarify a phrase in a comment
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Correct spelling

Most are code comments, but one case is a literal in a logging message.

There are a few grammar fixes too.
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* chanche MRO

* fix MRO resolution

* Migrate to f-strings in python-package/lightgbm/sklearn.py

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

* Update python-package/lightgbm/sklearn.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>

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

* Add suggestions from code review

* resolve conflicts

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

* Update sklearn.py
Co-authored-by: James Lamb <jaylamb20@gmail.com>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* include support for init_score

* use dataframe from init_score and test difference with and without init_score in local model

* revert refactoring

* initial docs. test between distributed models with and without init_score

* remove ranker from tests

* test value for root node and change docs

* comma

* re-include parametrize

* fix incorrect merge

* use single init_score and the booster_ attribute

* use np.float64 instead of float

* run isort in CI linting job

* workaround conda compatibility issues

* minor mypy type errors fixed

* fix some warnings from mypy

* fix 3 mypy warnings

* selectively ignored some mypy errors

* minor mypy type errors fixed

* minor mypy type errors fixed

* minor mypy type errors fixed

* added import

* Update python-package/lightgbm/callback.py

* Apply suggestions from code review

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

* Update dask.py

* Update sklearn.py

* got fit() working

* add predict()

* predict_proba()

* remove custom objective docs

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

* fix capitalization

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

* Update sklearn.py

* Update dask.py

* initial Dask docs

* fix MRO

* address review comments

* centralize Python-package logging in one place

* continue

* fix test name

* removed unused import

* enhance test

* fix lint

* hotfix test

* workaround for GPU test

* remove custom logger from Dask-package

* replace one log func with flags by multiple funcs

* fix docs

* Update basic.py

* Update engine.py

* [python-package] expand documentation on 'group' for ranking task

* add R package

* update Query Data section

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

* fix typo in group example

* regenerate parameters

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

* regenerate R docs
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Update setup.py

* Update .appveyor.yml

* Update .travis.yml

* Update .vsts-ci.yml

* Update __init__.py

* Update test.sh

* Update test_windows.ps1

* Update advanced_example.py

* Update requirements_base.txt

* Update conf.py

* Update conf.py

* Update test_engine.py

* Update utils.py

* Update dockerfile-r

* Update README.md

* Update dockerfile.gpu

* Update test_consistency.py

* Update basic.py

* Update compat.py

* Update engine.py

* Update sklearn.py

* Update sklearn.py

* Update callback.py

* Update setup.py

* Update __init__.py

* Update plotting.py

* Update sklearn.py

* Update engine.py

* Update compat.py

* Update callback.py

* Update basic.py

* Update compat.py

* Update basic.py

* Update basic.py

* Update compat.py

* Update compat.py

* Update plotting.py

* Update engine.py

* Update basic.py

* Update sklearn.py

* Update compat.py

* Update engine.py

* Update engine.py

* Update callback.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update sklearn.py

* Update sklearn.py

* Update plotting.py

* Update sklearn.py

* Update compat.py

* Update compat.py

* Update engine.py

* Update plotting.py

* Update sklearn.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update compat.py

* Update compat.py

* Update compat.py

* Update engine.py

* Update basic.py

* Update compat.py

* Update basic.py

* Update basic.py

* Update basic.py

* Update compat.py

* Update compat.py

* Update basic.py

* Update basic.py

* Update .vsts-ci.yml

* Update .vsts-ci.yml

* Update conf.py

* Revert "Update dockerfile-r"

This reverts commit 4ff6ffc7e3eeda24cc6a59a3bb0c973f02d9d71c.

* TST make sklearn integration test compatible with 0.24

* remove useless import

* remove outdated comment

* order import

* use parametrize_with_checks

* change the reason

* skip constructible if != 0.23

* make tests behave the same across sklearn version

* linter

* address suggestions

* [python] fix dangerous default for eval_at in LGBMRanker

* use a tuple

* five

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

* Refactors sklearn API to allow a list of evaluation metrics in the parameter eval_metric of the class (and subclasses of) LGBMModel. Also adds unit tests for this functionality

* Simplify expression to check whether the user passed one or multiple metrics to eval_metric parameter

* Simplify new tests by using custom metrics already defined in the test file

* Update docstring to reflect the fact that the parameter "feval" from the "train" and "cv" functions can also receive a list of callables

* Remove oxford comma from docstrings

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

* Use named-parameters to make sure code is compatible with future versions of scikit-learn

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

* Remove throwaway return value to make code more succinct
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* Move statement to group together the code related to feval

* Avoid modifying original args as it causes errors in scikit-learn tools

For details see: https://github.com/microsoft/LightGBM/pull/2619



* Consolidate multiple eval-metrics unit-tests into one test
Co-authored-by: German I Ramirez-Espinoza <gire@home>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

simplify start_iteration param for predict in Python and some code cleanup for start_iteration (#3288)

* simplify start_iteration param for predict in Python and some code cleanup for start_iteration

* revert docs changes about the prediction result shape

* [python] add start_iteration to python predict interface (#3058)

* Apply suggestions from code review

* Update lightgbm_R.h

* Apply suggestions from code review

* Apply suggestions from code review

* fix R interface

* update R documentation
Co-authored-by: Guolin Ke <guolin.ke@outlook.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>

* Update engine.py

* Update sklearn.py

* adding sparse support to TreeSHAP in lightgbm

* updating based on comments

* updated based on comments, used fromiter instead of frombuffer

* updated based on comments

* fixed limits import order

* fix sparse feature contribs to work with more than int32 max rows

* really fixed int64 max error and build warnings

* added sparse test with >int32 max rows

* fixed python side reshape check on sparse data

* updated based on latest comments

* fixed comments

* added CSC INT32_MAX validation to test, fixed comments

* modify attribute and include stacking tests

* backwards compatibility

* check sklearn version

* move stacking import

* Number of input features (#3173)

* Number of input features (#3173)

* Number of input features (#3173)

* Number of input features (#3173)

Split number of features and stacking tests.

* Number of input features (#3173)

Modify test name.

* Number of input features (#3173)

Update stacking tests for review comments.

* Number of input features (#3173)

* Number of input features (#3173)

* Number of input features (#3173)

* Number of input features (#3173)

Modify classifier test.

* Number of input features (#3173)

* Number of input features (#3173)

Check score.

* Revert "[ci][docs] temporarily pin Sphinx version (#3157)"

This reverts commit b3a84df5.

* removed duplicated docstrings

* update number of features attribute

Fixes issue related to https://github.com/scikit-learn/scikit-learn/issues/17353 (see SLEP010 https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep010/proposal.html

).

* Update sklearn.py

* set public attribute in fit method

Reverted ```n_features``` property, and inserted the public attribute ```n_features_in_```.

* Update documentation

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

* Revert "specify the last supported version of scikit-learn (#2637)"

This reverts commit d1002776.

* ban scikit-learn 0.22.0 and skip broken test

* fix updated test

* fix lint test

* Revert "fix lint test"

This reverts commit 8b4db0805fe7a9e7f7eb0be3eac231f85026d196.

* Add handling of RandomState object, which is standard for sklearn methods.

LightGBM expects an integer seed instead of an object.
If passed object is RandomState, we choose random integer based on its state to seed the underlying low level code.
While chosen random integer is only in the range between 1 and 1e10 I expect it to have enough entropy (?) to not matter in practice.

* Add RandomState object to random_state docstring.

* remove blank line

* Use property to handle setting random_state.
This enables setting cloned estimators with the set_params method in sklearn.

* Add docstring to attribute.

* Fix and simplify docstring.

* Add test case.

* Use maximal int for datatype in seed derivation.

* Replace random_state property with interfacing in fit method.
Derives int seed for C code only when fitting and keeps RandomState object as param.

* Adapt unit test to property change.

* Extended test case and docstring
Co-Authored-By: Nikita Titov <nekit94-08@mail.ru>

* Add more equality checks (feature importance, best iteration/score).

* Add equality comparison of boosters represented by strings.
Remove useless best_iteration_ comparison (we do not use early_stopping).

* fix whitespace

* Test if two subsequent fits produce different models

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

* add property: feature_name_ in lgb sklearn api

* modify the comments

* fix linting errors and add info about new attribute: feature_name_