GitLab

* 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

* add support of refit-decay

* add refit into c_api

* add test

* update document

* Update basic.py

* Update test_engine.py

* Update basic.py

* Update test_engine.py

* fix comments

* update test

* fix the comments

* Update test_engine.py

* add start_iteration in model saving

* fix test

* shuffle models ability

* fix bug

* update document

* refine

* Update engine.py

* Update basic.py

* fix comments

* fix comment

* refined num_iteration argument in python

* hotfix

* broadcast info about negative values in categorical features to python package

* update link to categorical_feature parameter

* refined random_state description

* use neutral alias and fixed desc of eval_at param, since metric can be not only ndcg

* simplified checks

* consider verbose alias

* fixed declaring function every loop iteration