From f402539ae3c8d3f60a8d83f56308c2d0f58850b6 Mon Sep 17 00:00:00 2001 From: Paul Koch Date: Mon, 13 Jan 2025 16:23:59 -0800 Subject: [PATCH] change max_leaves to a default of 2 for classification --- python/interpret-core/interpret/glassbox/_ebm/_ebm.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/interpret-core/interpret/glassbox/_ebm/_ebm.py b/python/interpret-core/interpret/glassbox/_ebm/_ebm.py index f07dc90a1..d87a43f1b 100644 --- a/python/interpret-core/interpret/glassbox/_ebm/_ebm.py +++ b/python/interpret-core/interpret/glassbox/_ebm/_ebm.py @@ -2815,7 +2815,7 @@ class ExplainableBoostingClassifier(ClassifierMixin, EBMModel): effectively making it location-agnostic. This can lead to overfitting, especially when the proportion of missing values is small. - `'gain'`: Choose the best leaf for the missing value contribution at each boosting step, based on gain. - max_leaves : int, default=3 + max_leaves : int, default=2 Maximum number of leaves allowed in each tree. monotone_constraints: list of int, default=None @@ -2978,7 +2978,7 @@ def __init__( min_cat_samples: Optional[int] = 10, cat_smooth: Optional[float] = 10.0, missing: str = "separate", - max_leaves: int = 3, + max_leaves: int = 2, monotone_constraints: Optional[Sequence[int]] = None, objective: str = "log_loss", # Overall