diff --git a/pimp/evaluator/fanova.py b/pimp/evaluator/fanova.py
index eb71ddb..42ec23b 100644
--- a/pimp/evaluator/fanova.py
+++ b/pimp/evaluator/fanova.py
@@ -14,6 +14,7 @@
 from ConfigSpace.configuration_space import ConfigurationSpace, Configuration
 from ConfigSpace.util import impute_inactive_values
 from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant
+from ConfigSpace.exceptions import ForbiddenValueError
 
 try:
     from fanova import fANOVA as fanova_pyrfr
@@ -92,14 +93,20 @@ def _preprocess(self, runhistory):
         if self.cs_contained_constant:
             configs = [Configuration(self.cs, vector=c.get_array()) for c in configs]
         X_non_hyper, X_prime = [], []
+        skipped_forbidden = 0
         for config in configs:
-            config = impute_inactive_values(config).get_array()
+            try:
+                config = impute_inactive_values(config).get_array()
+            except ForbiddenValueError:
+                skipped_forbidden += 1
+                continue
             X_prime.append(config)
             X_non_hyper.append(config)
             for idx, param in enumerate(self.cs.get_hyperparameters()):
                 if not (isinstance(param, CategoricalHyperparameter) or
                         isinstance(param, Constant)):
                     X_non_hyper[-1][idx] = param._transform(X_non_hyper[-1][idx])
+        self.logger.debug("Skipped %d forbidden configurations", skipped_forbidden)
         X_non_hyper = np.array(X_non_hyper)
         X_prime = np.array(X_prime)
         y_prime = np.array(self.model.predict_marginalized_over_instances(X_prime)[0])
diff --git a/pimp/evaluator/local_parameter_importance.py b/pimp/evaluator/local_parameter_importance.py
index fc28f0f..60a15d3 100644
--- a/pimp/evaluator/local_parameter_importance.py
+++ b/pimp/evaluator/local_parameter_importance.py
@@ -193,6 +193,7 @@ def run(self) -> OrderedDict:
                 added_inc = False
                 inc_at = 0
                 # Iterate over neighbors
+                skipped_forbidden_neighbors = 0
                 for unit_neighbor, neighbor in zip(neighborhood_dict[param][0], neighborhood_dict[param][1]):
                     if not added_inc:
                         if unit_neighbor > incumbent_array[index]:
@@ -207,13 +208,22 @@ def run(self) -> OrderedDict:
                     new_array = incumbent_array.copy()
                     new_array = change_hp_value(self.incumbent.configuration_space, new_array, param, unit_neighbor,
                                                 index)
-                    new_configuration = impute_inactive_values(Configuration(self.incumbent.configuration_space,
-                                                                             vector=new_array))
+                    try:
+                        new_configuration = impute_inactive_values(Configuration(self.incumbent.configuration_space,
+                                                                                 vector=new_array))
+                    except ForbiddenValueError:
+                        skipped_forbidden_neighbors += 1
+                        continue
                     mean, var = self._predict_over_instance_set(new_configuration)
                     performance_dict[param].append(mean)
                     overall_var[param].append(mean)
                     variance_dict[param].append(var)
                     pbar.update(1)
+                self.logger.debug("Skipped %d (of %d) forbidden neighbors", skipped_forbidden_neighbors,
+                        len(neighborhood_dict[param][0]))
+                if skipped_forbidden_neighbors == len(neighborhood_dict[param][0]):
+                    self.logger.debug("No valid neighbors found for %s, skipping.", param)
+                    continue
                 if len(neighborhood_dict[param][0]) > 0:
                     neighborhood_dict[param][0] = np.insert(neighborhood_dict[param][0], inc_at, incumbent_array[index])
                     neighborhood_dict[param][1] = np.insert(neighborhood_dict[param][1], inc_at, self.incumbent[param])