GitLab

* add n_estimators_ and n_iter_ post-fit attributes

* address review comments

* in predict(), respect params set via `set_params()` after fit()

* extract docs changes

[python][sklearn] add `__sklearn_is_fitted__()` method to be better compatible with scikit-learn API (#4636)

[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>

* Update __init__.py

* Update Python-API.rst

* Update engine.py

* Update test_utilities.py

* Update sklearn.py

* Update callback.py

* Update callback.py

* Update callback.py

* deprecate advanced args of `train()` and `cv()`

* update Dask test

* improve deducing

* address review comments

* deprecate `silent` and standalone `verbose` args. Prefer global `verbose` param

* simplify code

* Rephrase warning messages

* Reffer to string type as `str` and and commas in `list of ...` types

* update `libpath.py` too

* allow to pass some params as pathlib.Path objects

* fix lint

* improve indentation

* 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
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* Update tests/python_package_test/test_dask.py

_train_part model.fit args to lines, pt2
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* Update python-package/lightgbm/dask.py

_train_part model.fit args to lines pt3
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* Update tests/python_package_test/test_dask.py

dask_model.fit args to lines
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* Update tests/python_package_test/test_dask.py
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* Update python-package/lightgbm/dask.py

use is instead of id()
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update tests/python_package_test/test_dask.py
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* Update tests/python_package_test/test_dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* 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
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* Update python-package/lightgbm/dask.py
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* 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
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* dask custom eval note to f-string pt 2
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* 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
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* Clarify a phrase in a comment
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* 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
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* Update python-package/lightgbm/sklearn.py
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* 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
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* Update sklearn.py
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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
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* 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
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* fix typo in group example

* regenerate parameters

* Apply suggestions from code review
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* regenerate R docs
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* 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
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* Remove throwaway return value to make code more succinct
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* 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>