GitLab

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

* [ci] speed up if-else, swig, and lint conda setup

* add 'source activate'

* python constraint

* start removing cuda v1

* comment out CI

* remove more references

* revert some unnecessaary changes

* revert a few more mistakes

* revert another change that ignored params

* sigh

* remove CUDATreeLearner

* fix tests, docs

* fix quoting in setup.py

* restore all CI

* Apply suggestions from code review
Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* Apply suggestions from code review

* completely remove cuda_exp, update docs

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Co-authored-by: shiyu1994 <shiyu_k1994@qq.com>

* add rmse metric for new cuda version

* add Init for CUDAMetricInterface

* fix lint errors

* fix rmse and add l2 metric for new cuda version

* use CUDAL2Metric

* explicit template instantiation

* write result only with the first thread

* pre allocate buffer for output converting

* fix l2 regression with cuda metric evaluation

* weighting loss in cuda metric evaluation

* mark CUDATree::AsConstantTree as override

* add rmse metric for new cuda version

* add Init for CUDAMetricInterface

* fix lint errors

* initial work for boosting and evaluation with CUDA

* fix compatibility with CPU code

* fix creating objective without USE_CUDA_EXP

* fix static analysis errors

* fix static analysis errors

* Implement average precision score

* Fix lint errors

* Change name to average_precision

* Add to R-package list of metrics

* Empty commit to trigger CI jobs

* Change name to average_precision

* 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 auc-mu multiclass metric.

* Fix bug where scores are equal.

* Merge.

* Change name to auc_mu everywhere (instead of auc-mu).

* Fix comparison between signed and unsigned int.

* Change name to AUC-mu in docs and output messages.

* Improve test.

* Use prefix increment.

* Update R package.

* Fix style issues.

* Tidy up test code.

* Read all lines first then process.

* Allow passing AUC-mu weights directly as a list in parameters.

* Remove unused code, improve example and docs.

* fix metric alias

* fix format

* updated docs

* simplify alias in objective function

* move the alias parsing to config.cpp

* updated docs

* fix multi-class aliases

* updated regression aliases in docs

* fixed trailing space

* added all necessary includes - fixed build/include_what_you_use error

* fixed the order of includes (build/include_order)

* bring consistency and clearness into early_stopping_rounds desc, metric desc and implementation

* hotfix

* hotfix

* used NDCG as default metric for lambdarank task

* fixed missed methods at ReadTheDocs and changed default eval_metric

* leaved only unique metrics

* fixed comment

* [WIP] refine config

* [wip] ready for the auto code generate

* auto generate config codes

* use with to open file

* fix bug

* fix pylint

* fix bug

* fix pylint

* fix bugs.

* tmp for failed test.

* fix tests.

* added nthreads alias

* added new aliases from new config.h

* fixed duplicated alias

* refactored parameter_generator.py

* added new aliases from config.h and removed remaining old names

* fix bugs & some miss alias

* added aliases

* add more descriptions.

* add comment.

* added new aliases for regression_l2 to docs

* fixed new line

* fixed tweedie_variance_power description

* moved gamma and tweedie metrics to other regression metrics

* added new aliases for l2 to docs

* added new alias for l1 to docs

* added new alias for log loss to docs

* added new aliases for multiclass to docs

* added description for default value of metric param

* fixed link to poisson regression and capitalized regressions' names

* removed unused earlier alias type for gamma deviance

* added aliases for multiclass and multiclass_ova

* updated Quick-Start.rst according to Parameters.rst

* added cross-entropy into Features

* added aliases

[python] [docs] fixed objective in sklearn wrapper; added missed objectives & metrics to docs (#1059)

* added missed aliases for task parameter

* fixed indents

* added missed aliases and options for tree_learner parameter

* added missed objectives to docs

* fixed typo in Poisson parameter and its description

* fixed model_format parameter description

* added missed metrics to docs

* fixed sklearn objective

* fixed set_params

* fixed docs

* added missed options to objectives

* added note about ignore_column (#1061)

* add quantile metric.

* first draft.

* add "sqrt" transform in regression objective function.

* fix a bug.

* update parameter doc

* fix doc

* 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.

* RMSE (L2) -> MSE (true L2)

* Remove sqrt unneeded reference

* Square L2 test (RMSE to MSE)

* No square root on test

* Attempt to add RMSE

* many refactors.

* remove multi_loglossova.

* fix tests.

* avoid using lambda function.

* fix some format.

* reduce branching.

* Support Poisson regression

Close #233

* update docs

http://research.microsoft.com/en-us/um/people/zhang/INRIA/Publis/Tutorial-Estim/node24.html

* Add Huber loss

https://en.wikipedia.org/wiki/Huber_loss

* update

* update docs/Parameters.md

* update

Support multiclass classification (#53)