From b6cbfeec29927ffc4c46fe48e4fbf47bc9bcccc6 Mon Sep 17 00:00:00 2001 From: James Lamb Date: Sat, 9 Apr 2022 18:32:13 -0500 Subject: [PATCH 1/2] [ci] have no-response bot post as github-actions user (#5136) --- .github/workflows/no-response.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/no-response.yml b/.github/workflows/no-response.yml index 93d37bae40ea..a731941c21eb 100644 --- a/.github/workflows/no-response.yml +++ b/.github/workflows/no-response.yml @@ -20,4 +20,4 @@ jobs: Thank you for taking the time to improve LightGBM! daysUntilClose: 30 responseRequiredLabel: awaiting response - token: ${{ secrets.WORKFLOW }} + token: ${{ github.token }} From 5f57d6c673ee5f4c10e408868f98762edb062204 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pablo=20D=C3=A1vila=20Herrero?= Date: Sun, 10 Apr 2022 02:10:17 +0200 Subject: [PATCH 2/2] [docs] Document behaviour of the first linear estimator (#5132) * Document behaviour of the first linear estimator * Properly update docs Co-authored-by: Pablo-Davila --- docs/Parameters.rst | 2 ++ include/LightGBM/config.h | 1 + 2 files changed, 3 insertions(+) diff --git a/docs/Parameters.rst b/docs/Parameters.rst index 6a5729f7e8d5..c3859e76224f 100644 --- a/docs/Parameters.rst +++ b/docs/Parameters.rst @@ -664,6 +664,8 @@ Dataset Parameters - the linear model at each leaf includes all the numerical features in that leaf's branch + - the first tree has constant leaf values + - categorical features are used for splits as normal but are not used in the linear models - missing values should not be encoded as ``0``. Use ``np.nan`` for Python, ``NA`` for the CLI, and ``NA``, ``NA_real_``, or ``NA_integer_`` for R diff --git a/include/LightGBM/config.h b/include/LightGBM/config.h index 83c228fe5dc6..a7c254e5aa0d 100644 --- a/include/LightGBM/config.h +++ b/include/LightGBM/config.h @@ -586,6 +586,7 @@ struct Config { // desc = fit piecewise linear gradient boosting tree // descl2 = tree splits are chosen in the usual way, but the model at each leaf is linear instead of constant // descl2 = the linear model at each leaf includes all the numerical features in that leaf's branch + // descl2 = the first tree has constant leaf values // descl2 = categorical features are used for splits as normal but are not used in the linear models // descl2 = missing values should not be encoded as ``0``. Use ``np.nan`` for Python, ``NA`` for the CLI, and ``NA``, ``NA_real_``, or ``NA_integer_`` for R // descl2 = it is recommended to rescale data before training so that features have similar mean and standard deviation