GitLab

* Update dataset.cpp

* Update dataset.cpp

* refine categorical split

* add test

* better log for "Check max_depth and num_leaves"

The default log said "[LightGBM] [Warning] Accuarcy may be bad since you didn't set num_leaves." but the case max_depth²>num_leaves could also trigger this log.
Correction of a typo too : Accuarcy > Accuracy

* Update config.cpp

While in parallel training, when one worker have 0 data, then it will not execute ConstructHistogram.
if so, ptr_smaller_leaf_hist_data will not be 0 but the old data. that will get the wrong Histogram, and the wrong split info.

* Fix feature attributions for regression models and add Python bindings

* Address pylint issue

* Lazy fix missing tree depth info

* Attempt to address issue #807 Poisson regression objective.

* Fix coding style.

* Added label non-negative safety check.

* expose feature importance to c_api

* support type=gain

* remove dump model from examples and tests temporarily because it's unstable

* use double instead of float

* output warning when only set `max_depth`

* Remove check of max_depth

max_depth can take both positive and negative value

* Explain individual predictions using SHAP value feature attributions

* Address code review

* fix r random crash problem.

* fix R error msg.

* fix model feature importance

* fix appveryor test

* Revert "fix appveryor test"

This reverts commit 3a10a1723df5b8579e345d0da07638186257ec64.

* fix warning & boost_from_average_

* fix bug

* alter num_used_model

* finish the data loading part

* allow prediction.

* fix bug for decision type.

* finish split finding part

* fix bugs.

* bug fixed. add a test .

* fix pep8 .

* update documents.

* fix test bugs.

* fix a format

* fix import error in python test.

* disable missing handle in categorial features.

* fix a bug.

* add more tests.

* fix pep8

* fix bugs.

* remove the missing handle code for categorical feature.

* Created objectives and metrics xentropy and xentropy1

* Some coment and code cleanup.

* Added Kullback-Leibler version of metric. Changed some warning messages.

* Fixed sign error in KL-divergence calc.

* Removed __PRETTY_FUNCTION__.

* Fixed better name for alternative xentropy parameterization.
Documented details on the objectives / metrics in code comments.

* Common code for label interval checks. Cleanups.

* Use common utility for various weight property checks.

* Added code for customizable initial average to boost from.

* Fixed spelling error in aliases.

* Fixed nullptr check error in custom average.

* Added network code for customized init score.

* Restructured so that "standard" and "custom" init auto scores share aux.
function.

* Updated name for aux. automatic initial score fetcher.