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fix: use squared_error instead of deprecated mse criterion in tree tests #100

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fix: use squared_error instead of deprecated mse criterion in tree tests #100

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6 changes: 3 additions & 3 deletions numpy_ml/tests/test_trees.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -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,
Expand Down Expand Up @@ -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,
Expand Down