fixing some pipeline tests

Author: jarverha

tests/test_pipeline_powershap.py

@@ -177,7 +177,7 @@ def test_pipeline_catboost_class_standardscaler_powershap(dummy_classification):
     assert n_informative > 0, "No informative columns in the dummy data!"
 
     selector = PowerShap(
-        model=make_pipeline(StandardScaler, CatBoostClassifier(n_estimators=250, verbose=0)), power_iterations=15, automatic=False
+        model=make_pipeline(StandardScaler(), CatBoostClassifier(n_estimators=250, verbose=0)), power_iterations=15, automatic=False
     )
 
     selector.fit(X, y)
@@ -194,7 +194,7 @@ def test_pipeline_catboost_class_maxabsscalerr_robustscaler_powershap(dummy_clas
     assert n_informative > 0, "No informative columns in the dummy data!"
 
     selector = PowerShap(
-        model=make_pipeline(MaxAbsScaler, RobustScaler, CatBoostClassifier(n_estimators=250, verbose=0)), power_iterations=15, automatic=False
+        model=make_pipeline(MaxAbsScaler(), RobustScaler(), CatBoostClassifier(n_estimators=250, verbose=0)), power_iterations=15, automatic=False
     )
 
     selector.fit(X, y)

tests/test_shap_explainer.py

@@ -167,10 +167,8 @@ def test_get_pipeline_explainer():
 
     for model_class in model_classes:
         DummyScaler = FunctionTransformer(lambda x: x)
-
-        make_pipeline(DummyScaler, model_class)
-
-        explainer = ShapExplainerFactory.get_explainer(make_pipeline)
+        explainer = ShapExplainerFactory.get_explainer(make_pipeline(DummyScaler, model_class))
+        
         assert isinstance(explainer, PipelineExplainer)