GitLab

* always save the score of the first round in early stopping

fix #1971

* avoid using std::log on non-positive numbers

* remove unnecessary changes

* add tests

* Update test_sklearn.py

* enhanced tests

[tests][python] added tests for metrics' behavior and fixed case for multiclass task with custom objective (#1954)

* added metrics test for standard interface

* simplified code

* less trees

* less trees

* use dummy custom objective and metric

* added tests for multiclass metrics aliases

* fixed bug in case of custom obj and num_class > 1

* added metric test for sklearn wrapper

* [python] fix creating train_set in fit

https://github.com/Microsoft/LightGBM/blob/cc99f0d36ae929eb02b22a072823ab7c6d3155ab/python-package/lightgbm/sklearn.py#L519
may False even if valid_data[0] is X and valid_data[1] is y actually, because `check_X_y` might return copy of X and y.
https://scikit-learn.org/0.20/modules/generated/sklearn.utils.check_X_y.html

cf. https://github.com/Microsoft/LightGBM/pull/451

* use assertIn

* break huge lines in sklearn tests

* break huge line in plotting tests

* break huge lines in basic tests

* multiple enhancements in engine tests

* multiple enhancements in sklearn tests

* hotfixes

* break huge lines and use with statement in C API test

* make NDCG test more strict

* fix ndcg consistency.

* more stable sorts

* Update gbdt_model_text.cpp

* Update dataset.cpp

* Update gbdt_model_text.cpp

* fixed FutureWarning about cv default value

* fixed according to new check_estimator API

* fixed joblib warning

* added new aliases for params

* run helper/parameter_generator.py

* removed useless test

* ignore vim temporary files

* add importance_type arg to sklearn API

* update documentation info

* remote a trailing space

* remove trailing space (again :))

* add instructions on importance choices to sklearn API

* drop mention of constructor in the feature type setting

* adding a test for different feture types

* remove trailing spaces, make shorter assert in feature importance type handling test

* fixing style issue introduced with the new test

* removed excess import

* added tests for plotting trees in Python

* refined module_INSTALLED mechanism

* added note about that create_tree_digraph is better than plot_tree

* fixed grammar

* fixed params description in graph plotting functions

* clarified types of attributes in their descriptions

* increased readability of graphs by adding spaces

* added precision parameter to plot tree functions

* fixed docs

* reworker predict method of sklearn wrapper

* fixed encapsulation

* added test

* fixed consistency between docstring and params docs

* fixed verbose

* replaced predict_proba with predict in test

* fixed verbose again

* fixed fraction params descriptions

* added description of skip_drop and drop_rate constraints

* fixed subsample_freq consistency with C++ default value

* fixed nice look of params list

* made force splits json file example clickable

* fixed nice look of metrics list and added comma

* reduced warning in test about same param specified twice

* replaced pred_parameter with **kwargs in predict method

* added test for **kwargs in predict method

* fixed warnings

* fixed pylint

* added test for sklearn handle categorical features

* use raw X, y in sklearn wrapper in case of pandas.DataFrame

* fixed probs

* disabled logs from compilers; fixed #874

* fixed safe clear_fplder

* added windows folder to manifest.in

* added windows folder to build

* added library path

* added compilation with MSBuild from .sln-file

* fixed unknown PlatformToolset returns exitcode 0

* hotfix

* updated Readme

* removed return

* added installation with mingw test to appveyor

* let's test appveyor with both VS 2015 and VS 2017; but MinGW isn't installed on VS 2017 image

* fixed built-in name 'file'

* simplified appveyor

* removed excess data_files

* fixed unreadable paths

* separated exceptions for cmake and mingw

* refactored silent_call

* don't create artifacts with VS 2015 and mingw

* be more precise with python versioning in Travis

* removed unnecessary if statement

* added classifiers for PyPI and python versions badge

* changed python version in travis

* added support of scikit-learn 0.18.x

* added more python versions to Travis

* added more python versions to Appveyor

* reduced number of tests in Travis

* Travis trick is not needed anymore

* attempt to fix according to https://github.com/Microsoft/LightGBM/pull/880#discussion_r137438856

* fixed sklearn test on python 2.7

* commit to show that problem has been solved

* come back to python 3.6

* removed warnings check

* improved sklearn interface; added sklearns' tests

* moved best_score into the if statement

* improved docstrings; simplified LGBMCheckConsistentLength

* fixed typo

* pylint

* updated example

* fixed Ranker interface

* added missed boosting_type

* fixed more comfortable autocomplete without unused objects

* removed check for None of eval_at

* fixed according to review

* fixed typo

* added description of fit return type

* dictionary->dict for short

* markdown cleanup

* updated scikit-learn interface

* fixed better description

* updated set_params()

* removed backward compatibility

* removed excess lines

* replaced pop with setdefault

* added deprecated warnings

* added tests

https://docs.pytest.org/

* make test fail

* change default best_iteration to 0

* fix test

* change data_splitter to folds in cv

* update docs

* suppprt pandas categorical

* refine logic

* make default=auto

* fix train/valid categorical codes

* add test

* unify set _predictor

* fix tests

* fix warning

* support feature_name=int

* format python code with pep8

* **DO NOT MERGE** deliberately break rules to see what will happen during check

* Revert "**DO NOT MERGE** deliberately break rules to see what will happen during check"

This reverts commit 0db93cd7a43c7efa43a2112ada43d46c6f9115d9.

* fix format in test.py

* add docs for pep-8

* add @property to sklearn interface

* add deprecated; fix binary_metric

* support pickle

* add pickle/joblib test; change test_basic to unittest

* remove file for deepcopy

* fix tests

* test basic predict from file

* Revert "test basic predict from file"

This reverts commit 60d2c3158537fd56081f60f1d6d120cedd782887.

* test predict from file

* use tempfile for copy & pickle

* use tempfile w/o binary mode

* clean test

* remove other parameters in sklearn fit

* add dart parameters to sklearn init

* add troubleshooting

* use unittest

* update unittest version

* fix test_engine.py

* fix test_sklearn.py

* default eval_metric by subclass

* add test grid search

* remove verbose_eval

add learning rate to dart (#133)

* add feature importances in python; add pandas support

* solve best_iteration issue

1. merge python-package
2. add dump model to json
3. fix bugs
4. clean code with pylint
5. update python examples