clean up comments and if statement

alteryx · Jul 18, 2023 · 90fb578 · 90fb578
1 parent 121450f
commit 90fb578
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Showing 5 changed files with 7 additions and 11 deletions.
diff --git a/evalml/objectives/cost_benefit_matrix.py b/evalml/objectives/cost_benefit_matrix.py
@@ -48,7 +48,7 @@ def objective_function(
         Args:
             y_predicted (pd.Series): Predicted labels.
             y_true (pd.Series): True labels.
-            y_train (pd.Series): Training labels.
+            y_train (pd.Series): Ignored.
             X (pd.DataFrame): Ignored.
             sample_weight (pd.DataFrame): Ignored.
 

diff --git a/evalml/objectives/fraud_cost.py b/evalml/objectives/fraud_cost.py
@@ -49,7 +49,7 @@ def objective_function(
         Args:
             y_predicted (pd.Series): Predicted fraud labels.
             y_true (pd.Series): True fraud labels.
-            y_train (pd.Series): Training labels.
+            y_train (pd.Series): Ignored.
             X (pd.DataFrame): Data with transaction amounts.
             sample_weight (pd.DataFrame): Ignored.
 

diff --git a/evalml/objectives/lead_scoring.py b/evalml/objectives/lead_scoring.py
@@ -38,7 +38,7 @@ def objective_function(
         Args:
             y_predicted (pd.Series): Predicted labels.
             y_true (pd.Series): True labels.
-            y_train (pd.Series): Training labels.
+            y_train (pd.Series): Ignored.
             X (pd.DataFrame): Ignored.
             sample_weight (pd.DataFrame): Ignored.
 

diff --git a/evalml/objectives/standard_metrics.py b/evalml/objectives/standard_metrics.py
@@ -1041,7 +1041,7 @@ def objective_function(
 
 
 class MASE(TimeSeriesRegressionObjective):
-    """Mean absolute scaled error for time series regression. Scaled by 100 to return a percentage.
+    """Mean absolute scaled error for time series regression.
 
     Only valid if there exists a nonzero input in y_train. Otherwise, will throw a ValueError.
 
@@ -1068,12 +1068,9 @@ def objective_function(
         sample_weight=None,
     ):
         """Objective function for mean absolute scaled error for time series regression."""
-        # [0, 1, 1, 0] -- good
-        # [0, 0, 0, 0] -- bad
-
-        if (isinstance(y_train, pd.DataFrame) and (y_train.values == 0).all()) or (
-            isinstance(y_train, pd.Series) and (y_train == 0).all()
-        ):
+        if isinstance(y_train, np.ndarray):
+            y_train = pd.Series(y_train)
+        if (y_train.values == 0).all():
             raise ValueError(
                 "Mean Absolute Scaled Error cannot be used when "
                 "all training targets contain the value 0.",

diff --git a/evalml/tests/objective_tests/test_standard_metrics.py b/evalml/tests/objective_tests/test_standard_metrics.py
@@ -161,7 +161,6 @@ def test_negative_with_log():
 
 
 @pytest.mark.parametrize("objective_class", _all_objectives_dict().values())
-# @pytest.mark.parametrize("obj", [obj for obj in _all_objectives_dict().values()])
 def test_regression_handles_dataframes(objective_class):
     if not issubclass(objective_class, RegressionObjective):
         pytest.skip("Skipping non-regression objective")