GitLab

* Fix Invalid decision type error while plotting tree in Python

* Fix Invalid decision type error while plotting tree in Python (modified = to ==)

* Updated link to Development Guide in README.md

* Updated link to DevelopmentGuide in docs/README.md

* Revert "[R-package] Prevent remembering parameters (#796)"

This reverts commit c795e2c8e12e8fe989bde0ab4ee59c2301325814.

* Use model load/unload trick for free-ing up memory

* Missing comma

* Hand copy manual update (1/2)

* Hand copy manual update (2/2)

* Enable simple cloning of dataset

* Add remodel logical to Dataset

* Allow remodeling of data

* Missing comma

* Use name instead of assignment for R6 class

* There should be no need to deep copy ALL objects

* Force fork

* Better random CV + Group + Info handling

* Trailing comma missing

* Switch group fold to nrow

* Switch comparison from non-atomic to atomic

* Update Parameters.md

More readable "num_iterations" description.

* Update Parameters.md

Modified `num_iterations` description, in accordance with the review.

* Update Parameters.md

Modified "Parameters.md" in accordance with the review. 
More explicitly saying that "num_boost_round" is an input argument of the method (not a parameter, passed through the dict).

* params back up

* refine logic

* fix r random crash problem.

* fix R error msg.

* docs: add Advanced-Topic TOC

* docs: add title header to Advanced-Topic.md

* docs: convert development.md to development.rst

`pandoc --columns=200 -f markdown_github -t rst -o development.rst development.md`

* docs: update index.rst

* refine python codes

* fix appveryor test

* add note to feature_importances

* added test for training when both train and valid are subsets of a single lgb.Dataset object

* pep8 changes

* more pep8

* added test involving subsets of subsets of lgb.Dataset objects

* minor fix to contruction of X matrix

* even more pep8

* simplified test further

* 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

* added get_ref_chain function to Dataset object, used it in train() to compare if training and validation have common reference ancestors

* moved check of common ancestor reference from train() in engine.py to set_reference() in Dataset

* moved check of common ancestor reference from train() in engine.py to set_reference() in Dataset

* removed check for handle = None

* 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 warning for many core systems in Windows

* Add warning for not busy cores in Windows

* 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.