diff --git a/odte/Odte.py b/odte/Odte.py
index 8c9c059..1425aba 100644
--- a/odte/Odte.py
+++ b/odte/Odte.py
@@ -30,7 +30,7 @@ class Odte(BaseEnsemble, ClassifierMixin):
     def __init__(
         self,
         # n_jobs = -1 to use all available cores
-        n_jobs: int = 1,
+        n_jobs: int = -1,
         base_estimator: BaseEstimator = None,
         random_state: int = 0,
         max_features: Optional[Union[str, int, float]] = None,
@@ -141,8 +141,10 @@ class Odte(BaseEnsemble, ClassifierMixin):
         hyperparams_.update(dict(random_state=random_seed))
         clf.set_params(**hyperparams_)
         n_samples = X.shape[0]
-        # bootstrap
+        # initialize random boxes
+        random.seed(random_seed)
         random_box = check_random_state(random_seed)
+        # bootstrap
         indices = random_box.randint(0, n_samples, boot_samples)
         # update weights with the chosen samples
         weights_update = np.bincount(indices, minlength=n_samples)
diff --git a/odte/tests/Odte_tests.py b/odte/tests/Odte_tests.py
index 01ca3bc..0d1aa86 100644
--- a/odte/tests/Odte_tests.py
+++ b/odte/tests/Odte_tests.py
@@ -46,7 +46,9 @@ class Odte_test(unittest.TestCase):
         )
         for max_features in [4, 0.4, 1.0, None, "auto", "sqrt", "log2"]:
             tclf = Odte(
-                random_state=self._random_state, max_features=max_features
+                random_state=self._random_state,
+                max_features=max_features,
+                n_jobs=1,
             )
             tclf.fit(X, y)
             computed = tclf._get_random_subspace(X, y, tclf.max_features_)
@@ -149,6 +151,7 @@ class Odte_test(unittest.TestCase):
                     base_estimator=Stree(),
                     random_state=self._random_state,
                     n_estimators=3,
+                    n_jobs=1,
                 )
                 tclf.set_params(
                     **dict(
@@ -160,7 +163,7 @@ class Odte_test(unittest.TestCase):
                 expected = results.pop(0)
                 computed = tclf.fit(X, y).score(X, y)
                 # print(computed, splitter, max_features)
-                self.assertAlmostEqual(expected, computed)
+                self.assertAlmostEqual(expected, computed, msg=splitter)
 
     def test_generate_subspaces(self):
         features = 250