GitLab

* 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

* Fix coding style (#969)

Function names must be in the "Pascal Case" style.

* check_elements_interval_closed to CheckElementsIntervalClosed

* obtain_min_max_sum to ObtainMinMaxSum

* Change functions in common.h into template functions (#969)

* CheckElementsIntervalClosed

* ObtainMinMaxSum

These two functions were changed into template functions.

* Remove an unpreferable overload

* remove an overload of the function ObtainMinMaxSum

* Use stringstream to format T type

Function names must be in the "Pascal Case" style.

* check_elements_interval_closed to CheckElementsIntervalClosed

* obtain_min_max_sum to ObtainMinMaxSum

* 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.

* speed up the AUC metric by parallel sort.

* fix unix compile.

* fix template in unix.

* remove warning.

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

* Remove sqrt unneeded reference

* Square L2 test (RMSE to MSE)

* No square root on test

* Attempt to add RMSE

* refine prediction logic.

* fix test.

* fix out_len in training score of Dart.

* improve predict speed for high dimension data.

* many refactors.

* remove multi_loglossova.

* fix tests.

* avoid using lambda function.

* fix some format.

* reduce branching.

commit 70f88c54f6820d4c3824d97b34042c617fb21635
Author: Guolin Ke <i@yumumu.me>
Date:   Wed Feb 22 19:40:10 2017 +0800

    futher reduce guided

commit f54620b807c68f5ac6cef521d787ca2750efe464
Author: Guolin Ke <i@yumumu.me>
Date:   Wed Feb 22 19:32:36 2017 +0800

    avoid to use guided

* Support Poisson regression

Close #233

* update docs

* Added possibility to compile without openmp (useful for clang on Mac)

* Added CMake option to create dylib on MacOS

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

* finish R's c_api

* clean code

* fix sizeof pointer in 32bit system.

* add predictor class

* add Dataset class

* format code

* add booster

* add type check for expose function

* add a simple callback

* add all callbacks

* finish the basic training logic

* update docs

* add an simple training interface

* add basic test

* adapt the changes in c_api

* add test for Dataset

* add test for custom obj/eval functions

* fix python test

* fix bug in metadata init

* fix R CMD check

* add @property to sklearn interface

* add deprecated; fix binary_metric