fix bug in tests

Author: ravinkohli

autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/feature_preprocessing/SelectPercentileClassification.py

@@ -66,12 +66,12 @@ def get_hyperparameter_search_space(
                                                                           default_value="chi2",
                                                                           ),
     ) -> ConfigurationSpace:
-        value_range = ["mutual_info_classif"]
+        value_range = []
         if dataset_properties is not None:
             if (
                 dataset_properties.get("issigned") is False
             ):
-                value_range.append("chi2")
+                value_range.extend(["mutual_info_classif", "chi2"])
             if dataset_properties.get("issparse") is False:
                 value_range.append("f_classif")
         else:
@@ -81,6 +81,9 @@ def get_hyperparameter_search_space(
             warnings.warn(f"Given choices for `score_func` are not compatible with the dataset. "
                           f"Updating choices to {value_range}")
 
+        if len(value_range) == 0:
+            raise TypeError("`SelectPercentileClassification` is not compatible with the"
+                            " current dataset as it is both `signed` and `sparse`")
         score_func = HyperparameterSearchSpace(hyperparameter="score_func",
                                                value_range=value_range,
                                                default_value=value_range[-1],

autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/feature_preprocessing/SelectRatesRegression.py

@@ -17,7 +17,7 @@
 from autoPyTorch.utils.common import HyperparameterSearchSpace, add_hyperparameter
 
 
-class SelectPercentileRegression(autoPyTorchFeaturePreprocessingComponent):
+class SelectRatesRegression(autoPyTorchFeaturePreprocessingComponent):
     """
     Univariate feature selector by selecting the best features based on
     univariate statistical tests. Tests can be one of 'f_regression'

test/test_pipeline/components/preprocessing/test_feature_preprocessor.py

@@ -93,6 +93,14 @@ def test_pipeline_fit_include(self, fit_dictionary_tabular, preprocessor):
         in the include
         """
 
+        task_type = str(fit_dictionary_tabular['dataset_properties']['task_type'])
+        if (
+            ("Classification" in preprocessor or preprocessor == "LibLinearSVCPreprocessor")
+            and STRING_TO_TASK_TYPES[task_type] not in CLASSIFICATION_TASKS
+        ):
+            pytest.skip("Tests not relevant for {}".format(preprocessor.__class__.__name__))
+        elif "Regression" in preprocessor and STRING_TO_TASK_TYPES[task_type] not in REGRESSION_TASKS:
+            pytest.skip("Tests not relevant for {}".format(preprocessor.__class__.__name__))
         fit_dictionary_tabular['epochs'] = 1
 
         pipeline = TabularClassificationPipeline(