GitLab

[R-package] allow use of `categorical_features` in Dataset when raw data does not have column names (fixes #4374) (#5184)

* check for number of columns if data is matrixx for categorical indices check

* check for error when using a greater index than the number of columns

* apply suggestion
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* revert whitespace change

* check if is filename instead of matrix
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* check number of features when retrieving number of bins

* check for negative values

* lint

* skip auto-injected tasks at Azure Pipelines

* Update .vsts-ci.yml

* fix predict() params

* [R-package] ensure values in params override keyword arguments to predict() (fixes #4670)

* revert accidentally-introduced unrelated test changes

* Update R-package/tests/testthat/test_Predictor.R
Co-authored-by: José Morales <jose.morales@kavak.com>

* Update R-package/tests/testthat/test_Predictor.R
Co-authored-by: José Morales <jose.morales@kavak.com>

* linting

* remove nammes in shap test

* changes to tests
Co-authored-by: José Morales <jose.morales@kavak.com>

[python-package] remove 'fobj' in favor of passing custom objective function in params (fixes #3244) (#5052)

* feat: support custom metrics in params

* feat: support objective in params

* test: custom objective and metric

* fix: imports are incorrectly sorted

* feat: convert eval metrics str and set to list

* feat: convert single callable eval_metric to list

* test: single callable objective in params
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* feat: callable fobj in basic cv function
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: cv support objective callable
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* fix: assert in cv_res
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* docs: objective callable in params
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* recover test_boost_from_average_with_single_leaf_trees
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* linters fail
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* remove metrics helper functions
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* feat: choose objective through _choose_param_values
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: test objective through _choose_param_values
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: test objective is callabe in train
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: parametrize choose_param_value with objective aliases
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: cv booster metric is none
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* fix: if string and callable choose callable
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test train uses custom objective metrics
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: cv uses custom objective metrics
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* refactor: remove fobj parameter in train and cv
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* refactor: objective through params in sklearn API
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* custom objective function in advanced_example
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* fix whitespackes lint

* objective is none not a particular case for predict method
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* replace scipy.expit with custom implementation
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* test: set num_boost_round value to 20
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* fix: custom objective default_value is none
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* refactor: remove self._fobj
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* custom_objective default value is None
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* refactor: variables name reference dummy_obj
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* linter errors

* fix: process objective parameter when calling predict
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

* linter errors

* fix: objective is None during predict call
Signed-off-by: Miguel Trejo <armando.trejo.marrufo@gmail.com>

[python] Use predefined constant in feature importance type comparison instead of raw int literal (#5148)

* [R-package] reduce cost of repeated parameter alias checks

* formatting

* [ci] update to R 4.1.3 and use macOS-latest for R jobs (fixes #4990)

* update Windows version

* update docs env

* simplify r-package config

* Document behaviour of the first linear estimator

* Properly update docs
Co-authored-by: Pablo-Davila <Pablo-Davila@users.noreply.github.com>

* [ci] fail CI jobs earlier when installations fail

* more reliable link for R.pkg

* [ci] use lee-dohm/no-response to close stale issues (fixes #5060)

* only run once a day

* Update test_windows.ps1

* Update .appveyor.yml

* Update .appveyor.yml

* keep row names in prediction output

* fix test

* fix test

* fix test

* more tests for row names

* redo badly solved merge conflict

* comments

* update docs

* missing closing parentheses

* explicitly list assertions in each test

* move assertions back into shared function
Co-authored-by: James Lamb <jaylamb20@gmail.com>

* Update static_analysis.yml

* Update README.md

* Update README.md

* change prediction default to reshape=TRUE

* remove reshape argument

* comments

[R-package] Promote number of threads to top-level argument in `lightgbm()` and change default to number of cores (#4972)

* make `log_evaluation` callback pickleable

* make callback tests stricter

* make `record_evaluation` callback picklable

* make `log_evaluation` callback pickleable

* make callback tests stricter

* fix cuda exp with dense row wise

* disable usage of multi val group in cuda exp

* [python] allow to register any custom logger

* allow customizable logging method name; add unit test

* [python] allow to register any custom logger

* allow customizable logging method name; add unit test

* update tests

* fix lint error

* remove unused method

* fix docstring style
Co-authored-by: gongxudong <gongxudong@kuaishou.com>

* log warnings when number of bins of categorical features exceeds the configured maximum number of bins

* log only one warning information for all categorical features

* Add #include <memory> for unique_ptr

* remove useless param description

* rename weight -> weights

* add test for 'weights' argument

* Update R-package/R/lightgbm.R

* update docs
Co-authored-by: James Lamb <jaylamb20@gmail.com>