GitLab

* [python-package] fix mypy error about missing type hint in dask.py

* list of lists

* use different variable

* use append()

* Update __init__.py

* Update callback.py

* Update sklearn.py

* Update engine.py

* Update sklearn.py

* Update engine.py

* Update basic.py

* Update engine.py

* 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

* [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: Nikita Titov <nekit94-08@mail.ru>

* remove type hint on objective being callable
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* [c_api] Improve ANSI compatibility by avoiding <stdbool.h>

* fixes in response to CI linting

* inline NOLINT instead of separate test

* moving length declaration to non-ANSI C conditional

* [c_api] Align expected return type in `basic.py` with new c_api type.

* Faster categorical column names selection (#1)

* Faster categorical column names selection

Change slow and redundant dataframe query by select_dtypes into a dataframe.dtypes list comprehension

* Update compat with CategoricalDtype

* sort imports

* import CategoricalDtype from pandas.api.types

* add categorical import try/except

* Add 'nrounds' as an alias for 'num_iterations'

* Improve tests

* Compare against nrounds directly

* Fix whitespace lints

* initial changes

* initial version

* better handling of cases

* warn only with positive threshold

* remove early_stopping_threshold from high-level functions

* remove remaining early_stopping_threshold

* update test to use callback

* better handling of cases

* rename threshold to min_delta

enhance parameter description

update tests

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

* reduce num_boost_round in tests

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

* trigger ci
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-12@hotmail.com>

* respect objective aliases

* Update test_sklearn.py

* revert removal of blank lines

* add argument name which is being overwritten in warning message

* [docs] [dask] Add return information to Dask fit() docs (fixes #4402)

* put return before note

* 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

* Make dummy classes constructible with any arguments

* Update compat.py

* Improve error message for plot_metric with Booster

* Update error message

* update Guolin's e-mail in `setup.py`

* change maintainer's info

Co-authored-by: strobel <thaddaeus.strobel@ai4bd.com>
Co-authored-by: Nikita Titov <nekit94-12@hotmail.com>

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

* Update README.rst

* Update README.md

* Update Installation-Guide.rst

[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