diff --git a/tests/Stree_test.py b/tests/Stree_test.py
index e3736d5..32ebca6 100644
--- a/tests/Stree_test.py
+++ b/tests/Stree_test.py
@@ -144,17 +144,21 @@ class Stree_test(unittest.TestCase):
         """Check that element 28 has a prediction different that the current label
         """
         # Element 28 has a different prediction than the truth
-        decimals = 8
+        decimals = 5
         X, y = self._get_Xy()
         yp = self._clf.predict_proba(X[28, :].reshape(-1, X.shape[1]))
         self.assertEqual(0, yp[0:, 0])
         self.assertEqual(1, y[28])
-        self.assertEqual(round(0.29026400766, decimals), round(yp[0, 1], decimals))
+        self.assertAlmostEqual(
+            round(0.29026400766, decimals),
+            round(yp[0, 1], decimals),
+            decimals
+        )
 
     def test_multiple_predict_proba(self):
         # First 27 elements the predictions are the same as the truth
         num = 27
-        decimals = 8
+        decimals = 5
         X, y = self._get_Xy()
         yp = self._clf.predict_proba(X[:num, :])
         self.assertListEqual(y[:num].tolist(), yp[:, 0].tolist())
@@ -163,9 +167,10 @@ class Stree_test(unittest.TestCase):
                         0.30756427, 0.8318412,  0.18981198, 0.15564624, 0.25740655, 0.22923355,
                         0.87365959, 0.49928689, 0.95574351, 0.28761257, 0.28906333, 0.32643692,
                         0.29788483, 0.01657364, 0.81149083]
-        self.assertListEqual(
-            np.round(expected_proba, decimals=decimals).tolist(),
-            np.round(yp[:, 1], decimals=decimals).tolist())
+        expected = np.round(expected_proba, decimals=decimals).tolist()
+        computed = np.round(yp[:, 1], decimals=decimals).tolist()
+        for i in range(len(expected)):
+            self.assertAlmostEqual(expected[i], computed[i], decimals)
 
     def build_models(self):
         """Build and train two models, model_clf will use the sklearn classifier to