diff --git a/pysaliency/baseline_utils.py b/pysaliency/baseline_utils.py
index 370ef25..406ebe3 100644
--- a/pysaliency/baseline_utils.py
+++ b/pysaliency/baseline_utils.py
@@ -355,12 +355,17 @@ def _normalize_regularization_factors(args):
 
 
 class CrossvalMultipleRegularizations(object):
-    """ Class for computing crossvalidation scores of a fixation KDE with multiple regularization models"""
-    def __init__(self, stimuli, fixations, regularization_models: OrderedDict, crossvalidation, verbose=False):
+    """Class for computing crossvalidation scores of a fixation KDE with multiple regularization models
+
+    n_jobs: number of parallel jobs to use in cross_val_score
+    verbose: verbosity level for cross_val_score
+    """
+    def __init__(self, stimuli, fixations, regularization_models: OrderedDict, crossvalidation, n_jobs=None, verbose=False):
         self.stimuli = stimuli
         self.fixations = fixations
 
         self.cv = crossvalidation
+        self.n_jobs = n_jobs
         self.verbose = verbose
 
         X_areas = fixations_to_scikit_learn(
@@ -413,13 +418,13 @@ def score(self, log_bandwidth, *args, **kwargs):
 
 
 class CrossvalGoldMultipleRegularizations(CrossvalMultipleRegularizations):
-    def __init__(self, stimuli, fixations, regularization_models, verbose=False):
+    def __init__(self, stimuli, fixations, regularization_models, n_jobs=None, verbose=False):
         if fixations.subject_count > 1:
             crossvalidation_factory = ScikitLearnImageSubjectCrossValidationGenerator
         else:
             crossvalidation_factory = ScikitLearnWithinImageCrossValidationGenerator
 
-        super().__init__(stimuli, fixations, regularization_models, crossvalidation_factory=crossvalidation_factory, verbose=verbose)
+        super().__init__(stimuli, fixations, regularization_models, crossvalidation_factory=crossvalidation_factory, n_jobs=n_jobs, verbose=verbose)
 
 
 # baseline models