GitLab

[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

* add warnings for override parameters of Dataset

* fix pep8

* add feature_penalty

* refactor

* add R's code

* Update basic.py

* Update basic.py

* fix parameter bug

* Update lgb.Dataset.R

* fix a bug

* added get_data method

* hotfix

* added warning for other data types

* reworked according to review comments

* minor addition to FAQ

* added test

* [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

* disabled early stopping in dart mode

* check dart mode during the init phase of early_stop callback

* add pandas_categorical to returned json

* save pandas_categorical to model file

* added regression test

* removed excess conversion to list

* removed deprecated line

* hotfix

* removed misleading note about best_iteration

* Update engine.py

* Update Python-Intro.rst

* Updated Engine.py

* Updated Python-Intro.rst

* add article 'the best', break huge line and remove excess empty line

* added docstring style test and fixed errors in existing docstrings

* hotfix

* hotfix

* fix grammar

* hotfix

* downgrade Xcode version on Azure

* fixed docs and warning

* Fixed some typos in Python API Docs

* FixTypo changed validation set -> sets

* copy old Booster's attributes to new one in refit method

* fixed according to review comment

* raise error in case of null objective

* fix indices type in csr and csc

* fix

* add indexs in shuffle model.

* fix pep

* fix bug

* fixed FutureWarning about cv default value

* fixed according to new check_estimator API

* fixed joblib warning

* break extremely large lines in basic.py

* break extremely large lines in callback.py

* break extremely large lines in engine.py

* break extremely large lines in sklearn.py

* hotfixes

* added sklearn splitter classes in cv function

* added tests

* warning on categorical feature with sparse values

* [docs] categorical features note

* pass params to predictor

* hotfix

* added test for pandas label of Dataset

* fix when label type is pandas DataFrame; document possible pandas Series type

* fix ndcg group

* fix ndcg

* pass params to _InnerPredictor in train and cv

* fixed verbosity param description

* treat silent param as Fatal log level

* create Dataset in refit method silently

* do not overwrite verbose param by silent argument

* use kwargs in tree plotting functions

* relaxed version

* added possibility to predict numpy array with nrow > max_int32

* save memory more efficient

* better variable name

* added possibility to predict scipy.sparse.csr matrix with nrow > max_int32

* added possibility to predict scipy.sparse.csc matrix with nrow > max_int32

* reworked numpy array case

* bring consistency and clearness into early_stopping_rounds desc, metric desc and implementation

* hotfix

* hotfix

* used NDCG as default metric for lambdarank task

* fixed missed methods at ReadTheDocs and changed default eval_metric

* leaved only unique metrics

* fixed comment

* added NumberOfTotalModel and NumModelPerIteration to C_API and python-package

* fixed tests

* added tests for current_iteration, num_trees, num_model_per_iteration methods

* break huge line in test

* hotfix