GitLab

* 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

* 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

* 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.

* add draft of RF.

* fix score bugs.

* fix scores.

* fix tests.

* update document

* fix GetPredictAt

* avoid threshold inf

* use __save_model_to_string for feature importance

* Revert "use __save_model_to_string for feature importance"

This reverts commit dca6a85fb3d89866eb56eb0c9ca103ada4d92b53.

* fix multi-threading.

* fix name style.

* support in CLI version.

* remove warnings.

* Not default parameters.

* fix if...else... .

* fix bug.

* fix warning.

* refine c_api.

* fix R-package.

* fix R's warning.

* fix tests.

* fix pep8 .

* translate model to if-else

* support multiclass and predictleaf

* remove java option for now

* support multi-thread

* add task:convert_model