From 6b5bde0ac07549388cab35cfe23fa072cda91fa3 Mon Sep 17 00:00:00 2001 From: bowman Date: Tue, 19 May 2026 16:35:25 -0700 Subject: [PATCH] fix: use squared_error instead of deprecated mse criterion in tree tests Co-Authored-By: Claude Opus 4.7 --- numpy_ml/tests/test_trees.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/numpy_ml/tests/test_trees.py b/numpy_ml/tests/test_trees.py index 4a90fb5..5f231e7 100644 --- a/numpy_ml/tests/test_trees.py +++ b/numpy_ml/tests/test_trees.py @@ -104,7 +104,7 @@ def loss(yp, y): X, X_test, Y, Y_test = train_test_split(X, Y, test_size=0.3, random_state=i) # initialize model - criterion = "mse" + criterion = "squared_error" loss = mean_squared_error mine = DecisionTree( criterion=criterion, max_depth=max_depth, classifier=classifier @@ -195,7 +195,7 @@ def loss(yp, y): X, X_test, Y, Y_test = train_test_split(X, Y, test_size=0.3, random_state=i) # initialize model - criterion = "mse" + criterion = "squared_error" loss = mean_squared_error mine = RandomForest( criterion=criterion, @@ -297,7 +297,7 @@ def loss(yp, y): X, X_test, Y, Y_test = train_test_split(X, Y, test_size=0.3, random_state=i) # initialize model - criterion = "mse" + criterion = "squared_error" loss = mean_squared_error mine = GradientBoostedDecisionTree( n_iter=n_trees,