GitLab

* bump images

* updated linkchecker's config

* test: switch compilers

* switch compilers back

* new version number after release

* Update .appveyor.yml

* Update DESCRIPTION

* Update DESCRIPTION

* bump minor version

* Fix bug where small values of max_bin cause crash.

* Revert "Fix bug where small values of max_bin cause crash."

This reverts commit fe5c8e2547057c1fa5750bcddd359dd7708fab4b.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Add functionality to force bin thresholds.

* Fix style issues.

* Use stable sort.

* Minor style and doc fixes.

* Change binning behavior to be same as PR #2342.

* Use different bin finding function for predefined bounds.

* Fix style issues.

* Minor refactoring, overload FindBinWithZeroAsOneBin.

* Fix style issues.

* Fix bug and add new test.

* Add warning when using categorical features with forced bins.

* Pass forced_upper_bounds by reference.

* Pass container types by const reference.

* Get categorical features using FeatureBinMapper.

* Fix bug for small max_bin.

* Move GetForcedBins to DatasetLoader.

* Find forced bins in dataset_loader.

* Minor fixes.

* added installation guide with Homebrew

* hotfix

* update wording to separate install and build cases

* Fix integer overflow https://github.com/microsoft/LightGBM/issues/2357

* Use 2 spaces not 4

* Move constant the config.h
Move check outside the max_depth check

* Move the max leaves check to config.h

* Remove unnecessary check

* avoid copy where possible

* use precise type for importance type

* removed pointless code

* simplify sparse pandas Series conversion

* more memory savings

* always force type conversion for 1-D arrays

* one more copy=False

* Update feature_histogram.hpp

* Update feature_histogram.hpp

* refactoring

* fix style

* fix style

* Update cost_effective_gradient_boosting.hpp

* Update serial_tree_learner.cpp

* Update serial_tree_learner.h

* fix style

* update vc project

* Update cost_effective_gradient_boosting.hpp

* Fix bug where small values of max_bin cause crash.

* Revert "Fix bug where small values of max_bin cause crash."

This reverts commit fe5c8e2547057c1fa5750bcddd359dd7708fab4b.

* Add json files for forced bin example.

* Add second json file.

* add missing JNI exception checks to fix warnings

* updated based on comments

* removed rethrow logic

* replace tabs with spaces

* make dump_text() private

* updated test

* fix

* fix the bug

* refined order of includes

* hotfix

* fix many cpp lint errors

* indent

* fix bug

* fix more

* fix gpu

* more fixes

* added cpplint heck

* removed TODO from code

* change order of checks

* at least 2 features are chosen in subcolumn

* Update serial_tree_learner.cpp

* rounding

* fix bug

* fix include

* style minor fixes

* added editorconfig

* updated editorconfig

* Bug fix for first_metric_only if the first metric is train metric.

* Update bug fix for feval issue.

* Disable feval for first_metric_only.

* Additional test items.

* Fix wrong assertEqual settings & formating.

* Change dataset of test.

* Fix random seed for test.

* Modiry assumed test result due to different sklearn verion between CI and local.

* Remove f-string

* Applying variable  assumed test result for test.

* Fix flake8 error.

* Modifying  in accordance with review comments.

* Modifying for pylint.

* simplified tests

* Deleting error criteria `if eval_metric is None`.

* Delete test items of classification.

* Simplifying if condition.

* Applying first_metric_only for sklearn wrapper.

* Modifying test_sklearn for comforming to python 2.x

* Fix flake8 error.

* Additional fix for sklearn and add tests.

* Bug fix and add test cases.

* some refactor

* fixed lint

* fixed lint

* Fix duplicated metrics scores to pass the test.

* Fix the case first_metric_only not in params.

* Converting metrics aliases.

* Add comment.

* Modify comment for pylint.

* Modify comment for pydocstyle.

* Using split test set for two eval_set.

* added test case for metric aliases and length checks

* minor style fixes

* fixed rmse name and alias position

* Fix the case metric=[]

* Fix using env.model._train_data_name

* Fix wrong test condition.

* Move initial process to _init() func.

* Modify test setting for test_sklearn & training data matching on callback.py

* test_sklearn.py
-> A test case for training is wrong, so fixed.

* callback.py
-> A condition of if statement for detecting test dataset is wrong, so fixed.

* Support composite name metrics.

* Remove metric check process & reduce redundant test cases.

For #2273 fixed not only the order of metrics in cpp, removing metric check process at callback.py

* Revised according to the matters pointed out on a review.

* increased code readability

* Fix the issue of order of validation set.

* Changing to OrderdDict from default dict for score result.

* added missed check in cv function for first_metric_only and feval co-occurrence

* keep order only for metrics but not for datasets in best_score

* move OrderedDict initialization to init phase

* fixed minor printing issues

* move first metric detection to init phase and split can be performed without checks

* split only once during callback

* removed excess code

* fixed typo in variable name and squashed ifs

* use setdefault

* hotfix

* fixed failing test

* refined tests

* refined sklearn test

* Making "feval" effective on early stopping.

* allow feval and first_metric_only for cv

* removed unused code

* added tests for feval

* fixed printing

* add note about whitespaces in feval name

* Modifying final iteration process in case valid set is  training data.

* updated default value for precision in plot_importance function

* fixed typo

* updated example notebook

* update

* fix a bug

* Update config.h

* Update Parameters.rst

* keep consistent state for Dataset fields

* hotfix

* Some basic changes to the plot of the trees to make them readable.

* Squeezed the information in the nodes.

* Added colouring when a dictionnary mapping the features to the constraints is passed.

* Fix spaces.

* Added data percentage as an option in the nodes.

* Squeezed the information in the leaves.

* Important information is now in bold.

* Added a legend for the color of monotone splits.

* Changed "split_gain" to "gain" and "internal_value" to "value".

* Sqeezed leaves a bit more.

* Changed description in the legend.

* Revert "Sqeezed leaves a bit more."

This reverts commit dd8bf14a3ba604b0dfae3b7bb1c64b6784d15e03.

* Increased the readability for the gain.

* Tidied up the legend.

* Added the data percentage in the leaves.

* Added the monotone constraints to the dumped model.

* Monotone constraints are now specified automatically when plotting trees.

* Raise an exception instead of the bug that was here before.

* Removed operators on the branches for a clearer design.

* Small cleaning of the code.

* Setting a monotone constraint on a categorical feature now returns an exception instead of doing nothing.

* Fix bug when monotone constraints are empty.

* Fix another bug when monotone constraints are empty.

* Variable name change.

* Added is / isn't on every edge of the trees.

* Fix test "tree_create_digraph".

* Add new test for plotting trees with monotone constraints.

* Typo.

* Update documentation of categorical features.

* Typo.

* Information in nodes more explicit.

* Used regular strings instead of raw strings.

* Small refactoring.

* Some cleaning.

* Added future statement.

* Changed output for consistency.

* Updated documentation.

* Added comments for colors.

* Changed text on edges for more clarity.

* Small refactoring.

* Modified text in leaves for consistency with nodes.

* Updated default values and documentaton for consistency.

* Replaced CHECK with Log::Fatal for user-friendliness.

* Updated tests.

* Typo.

* Simplify imports.

* Swapped count and weight to improve readibility of the leaves in the plotted trees.

* Thresholds in bold.

* Made information in nodes written in a specific order.

* Added information to clarify legend.

* Code cleaning.

* avoid nan and inf in weight/label/init_score

* use prefix increment